What do I need to learn?

Content First taught Number of marks Hypotheses: Alternative and null Unit 1

Independent and Dependent variables, operationalisation of variables

Unit 1

Research design: Independent groups, repeated measures and matched pairs

Unit 1

Correlational studies Unit 2

Cross-sectional and longitudinal designs Unit 2

Extraneous and confounding variables, situational variables, participant variables, experimenter effects, demand characteristics

Unit 1

Order effects, counter-balancing and randomization

Unit 1

Sampling Techniques Unit 1

Quantitative and Qualitative data Unit 1

Nominal, ordinal, interval and ratio data Unit 2

Primary and Secondary Data Unit 4

Human Ethics Unit 1

Animal Ethics Unit 2

Ethics use of children in research Unit 3

Objectivity, reliability, validity Unit 1

Measures of central tendency: mean, median and mode

Unit 1

Measures of dispersion/spread: range and standard deviation

Unit 1

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Inferential Statistics and critical value tables Unit 2

Probability and Significance Unit 2

Laboratory Experiments Unit 1

Field Experiments Unit 1

Natural Experiments Unit 1

Experiments using animals Unit 2

Surveys: Questionnaires and Interviews Unit 1

Case studies Unit 2

Twin Studies Unit 2

Adoption Studies Unit 2

MRI scans Unit 2

PET scans Unit 2

Observations Unit 2

Cross-cultural research Unit 3

Content Analysis Unit 3

There is a lot to learn, but it is not impossible! Use your knowledge from the Cognitive Approach to help you revise:

o Revise in ‘chunks’ – do not try to learn too much at once – it is easy to get confusedo Deep processing is best – do not simply read the information, do something with it. Spider diagrams,

flash cards, post-it notes for definitions are all helpful. If you know something well enough to explain it to someone else without notes then you will be fine in the exam

o Use cues to help you remember such as mnemonics or includes pictures on your spider diagrams which can act as a visual cue in the exam

o Test yourself – especially with past exam questions, you know the style of question that will be asked so make them up, you have my email address so you can email me questions that you complete and I will mark them and send them back to you with comments (jkirk@pensbyhigh.wirral.sch.uk)

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o Use the Learning Environment – there is extra information on there, including podcasts for auditory learners. I have also set up a revision forum where you can post questions/ share your frustrations and I and you can answer any questions

Methodology is the study of research methods. You may ask why we should study research methods – the reason is that it helps you to be able to carry out your own research and also you can evaluate how useful or accurate other research.

In this booklet we will look at the many different methods used in Psychology, both qualitative and quantitative, look at designing a study and ways in which the results of a study can be analysed using descriptive and inferential statistics.

This booklet is designed to be used throughout your Psychology course. Take notice of the first 2 pages and the column which says ‘First Taught’. If you are studying for your first exam in the January of your AS year you will only need to look at the topics first taught for Unit 1. If you are revising in the January of your A2 year you will need to revise topics taught for Units 1, 2 and 3.

If we look at the studies we have covered so far in Psychology we can say two things

The researcher manipulated one thing The researcher measured the effect this manipulation had on something else

This means at the heart of all study there are (at least) two things that vary, this is why they are called variables.

Independent Variable/s (IV) is the thing which the researcher manipulates.

Dependent Variable/s (DV) is the variable which the researcher measures to see how much of an effect their manipulation of the independent variable has had.

One way of seeing an experiment is as a study of cause and effect. We have one variable (the IV) which causes an effect in a second variable (the DV). The researcher manipulates the IV and this causes an effect. It is the DV the researcher then measures.

Activity Independent and Dependent Variables

To check your understanding of IVs and DVs, descriptions of psychological studies have been provided below. In each case, try to work out what the IV and DV are. The first example has been completed for you.

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1. Researchers have investigated the effect of taking cannabis on driving. An experiment is described where the amount of cannabis taken by the participant was either a high or a low dose, to see what effect it had on driving behaviour.

The IV = amount of cannabis taken (high or low dose)

The DV = driving behaviour

2. The Home Office wanted to know whether identification of suspects at video identification parades was different from that at traditional, live identification parades. They asked a psychologist to conduct an experiment to investigate this. The psychologists showed 40 participants a staged crime and a week later asked half to identify the suspect from a video identification parade and half from a live identification parade. The psychologist recorded whether each participant identified the suspect or a ‘foil’ (another person placed in the ID parade).

IV =

DV =

3. A psychologist was studying musical creativity in children. They recruited 30 10 year olds and asked half of them to compose a piece for the recorder by themselves and the other half to compose in groups of three. Each piece of music was rated for creativity by the researcher.

IV =

DV =

4. A researcher wanted to find out if the emotive nature of a word affected how memorable it was. They produced a list of 50 words, half of which were highly emotive (e.g. love, war) and half of which were non-emotive (table, carpet etc…) and asked 20 participants to read and memorise the words. 10 minutes after reading the words each participant was asked to recall as many as they words as they could remember.

IV =

DV =

5. A psychologist employed by a supermarket was asked to study the effects of playing background music on shopping. The psychologist was allowed to use a supermarket for two weeks. During the first week, the psychologist played music through the supermarket’s PA system and recorded how much money the supermarket took. During the second week they again recorded sales, but this time played no music.

IV =

DV =

A note about Quasi-experiments

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We have been talking about experiments being defined by a researcher manipulating an IV and measuring the DV, however, sometimes the researcher does not themselves directly manipulate the IV. For example if someone was interested in looking at sex differences in aggression, they could not randomly allocate people into the two conditions (male and female) because you either are male or female. The same can be said of other characteristics such as height, age, IQ etc… Another example would be comparing how happy people who have committed a crime are in their marriage compared to those who have not committed a crime – again these people cannot be randomly allocated as you either have committed a crime or you have not.

The aim of a study is what the researcher is wanting to find out – this could be in the form of a question e.g. Does drinking alcohol have an effect upon driving behaviour?

From the aim a researcher has to develop an alternative hypothesis (called an experimental hypothesis in an experiment). A hypothesis is a testable statement which expresses the relationship you believe to exist (in a correlational study) or the difference between conditions in an experiment. In order to word an experimental hypothesis correctly you must know what the IV and DV are.

The alternative hypothesis (or H1) can be one tailed (directional) or two tailed (non-directional). A two-tailed or non-directional hypothesis states that manipulation of the IV will affect the DV but does not state in which direction, whereas a one-tailed or directional hypothesis is more precise about the expected outcome of the study.

An example of a two-tailed/ non-directional hypothesis:

H1 Exercise effects mood

This is two-tailed because it does not tell us whether exercise improves or impairs mood.

An example of a one-tailed/ directional hypothesis

H1 Exercise improves mood

This is one-tailed because it clearly shows that the IV (exercise) is affecting the DV (mood) and in which direction (improves)

Operationalising variables

The above hypotheses are still not sufficient for research as they do not state how the IV is to be manipulated and the DV measured. For example you need to fully define or operationalise how you will measure mood and how you will manipulate exercise – one person’s idea of exercise may literally be a walk in the park (sorry!) to someone else.

An example of a fully operationalised alternative hypothesis

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H1 Participants who take two 1 hour aerobics classes a week will have a higher score on the Happiness Indices than participants who do no aerobics classes

Here you can see that exercise has been defined as two aerobics classes – half the participants could be randomly assigned to this group and half to the control group who do not exercise. Obviously you would have to make it clear to the participants that they are to do no other exercise and the same to the exercise group. The ‘Happiness Indices’ is a made up questionnaire, however, there are questionnaires that exist which measure with some accuracy a person’s mood.

On the left is a two-tailed hypothefish, can you tell which direction it will swim? On the right is a one-tailed hypothesis swimming in an easterly direction.

Below is a diagram which should help you be able to write your own hypotheses:

The Null Hypothesis

One last thing you need to know about hypotheses is that the alternative hypothesis is not what is actually tested when Psychologists carry out research. They actually carry out statistical analysis on the null hypothesis which states that there will be no difference between the conditions and that any difference will be due to chance. Statistical tests work out whether your results are significant and include the likelihood that the results could

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have occurred by chance. If we take the example from before with exercise and mood the null hypothesis would be:

H0 There will be no difference in the scores of participants on the Happiness Indices whether they have 2 aerobics classes a week or none. Any difference will be due to chance.

If the results of a study are significant, the null hypothesis is rejected. If the results are not significant the null hypothesis is accepted.

Activity: Aims and Hypotheses

For each of the aims below, write down two versions of an alternative hypothesis, a directional and a non-directional one.

1. To find out if males or females eat more chocolate.2. To test whether older or younger children are better at judging the number of sweets in a jar.

3. To see whether recall of words can be affected by the use of verbal cues.

4. To investigate the likelihood of people sleeping for longer when they have been exercising

Read the questions below and write out an alternative and a null hypothesis. State whether the hypothesis you choose is directional or non-directional.

1. Are younger people more likely to be helpful than older people?

2. Are scientists less likely to hold religious beliefs than non-scientists?

3. Do dogs learn tricks faster than cats?

4. Do boys and girls differ in their ability at spatial tasks?

5. Are children more likely to imitate their parents than other adults?

6. Does emotional state affect memory?

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The design of an experiment is the way in which participants are allocated to perform in different levels of the independent variable. The possible designs are Independent Groups, Repeated Measures/ Groups and Matched Pairs.

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Activity Experimental Design

Below are descriptions of five psychological studies. In each case state whether the design is repeated measures of independent groups. You can also try to spot the IV and DV if you wish.

1. A developmental psychologist conducted an experiment to compare the response time of 5-year-old and 1—year-old children. Each child was asked to push a button on a computer keyboard every time a large blue square appeared on the screen.

Design =

2. 20 participants were recruited by a researcher who was studying whether taking an exam increased levels of stress. 10 participants were asked to complete a math’s test and 10 participants were asked to read a magazine article. After this task all of the participants completed an Anxiety Inventory, which yielded a score indicating stress levels.

Design =

3. A researcher conducted an experiment to see whether moving faces would be recognized more accurately than static images of faces. 30 participants were shown a videotape containing 18 faces, 9 of which were shown turning from side to side and 9 of which were static. 10 minutes after watching the video, the participants were shown a photo-array of 36 faces and asked to pick out any they had seen in the video.

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Matched Pairs DesignThese are used where a repeated measures design is not possible because performing one condition of the IV would influence performance on the other (e.g. in a problem solving experiment where a clue is given. Pps are matched in pairs across characteristics e.g. IQ and one member of each pair is allocated to each condition

Advantages No order effects Participant variables partly

controlled Can use repeated measures

statistical tests which are more powerful

Disadvantages Difficult to find perfect matches

(the most perfect are MZ twins) Time consuming Loss of one participant means

loss of the pair

Design =

4. It has been suggested that small groups of people tend to make more ‘risky’ or ‘extreme’ decisions than individuals. A researcher recruited 30 people and gave them descriptions of 5 court cases that required a financial settlement. Each participant first worked on their own to arrive at an amount and then formed a group of 10 participants an arrived at a group decision as to that amount.

Design =

5. It is a commonly held belief that people are more likely to buy a product if it is presented by an attractive person. To test this belief, a researcher constructed adverts for a new brand of toothpaste. In half of the adverts the person using the toothpaste was rated as very attractive by a panel of 10 judges and in the other half the toothpaste user was rated as average attractive. The researcher showed 100 people 1 of the adverts (50 saw the very attractive person and 50 the average person) and asked them to give a score of between 1 (very unlikely) and 10 (very likely) to indictate how likely they would be to buy the toothpaste.

Design =

Finished?? Why not go back to the IV and DV activity and identify the design used in those experiments!

Order effects occur when participants take part in all experimental conditions (such as in a repeated measures design). Participants may become better through practice or worse through fatigue (tiredness).

You can control order effects through counterbalancing – this is where half of the participants do condition 1 first and then condition 2, the other half do condition 2 first and then condition 1. This works as the participants now are not always fresh and naïve for condition 1 and tired and practiced for condition 2. A similar result can be achieved through randomization. This is where participants are randomly assigned to condition 1 or two first by tossing a coin or pulling names out of a hat.

You can also control for order effects by making sure that enough time has elapsed between each condition so that learning is forgotten and fatigue is overcome.

Extraneous variables are any variable, except the IV, that can have an influence on your findings. Extraneous variable affect a study over both levels of the IV. Worse are confounding variables, they are another variable which occur on one level of the IV and can have a direct impact on the independent variables.

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Situational variables are extraneous variables to do with the environment or situation in which your study takes place. Environmental conditions such as time of day, noise, heat, weather etc… may affect the results and should be controlled.

Participant variables are where differences in the participants themselves may affect the results. Some people are more motivated, some are more easily distracted etc… The best way to control for participant variables is by using a repeated measures design where the presentation of each condition is counterbalanced or by using a matched pairs design.

Activity Extraneous and Confounding variables

Look back at the descriptions of studies in the sections on Independent and Dependent variables and Research design. Try to identify any other variables which could influence the outcome of the results and if possible measures you would introduce to control this.

Activity Quick Test

Which of the following statements are true?

1. The independent variable is manipulated by the experimenter2. The independent variable is measured by the experimenter3. The independent variable is the causal factor in our ‘cause and effect’ relationship4. The independent variable is the effect in our ‘cause and effect’ relationship5. The dependent variable is the causal factor in our ‘cause and effect’ relationship6. The dependent variable is the outcome measured by the experimenter7. The dependent variable is manipulated by the experimenter8. The dependent variable is the effect in our ‘cause and effect’ relationship9. Confounding variables are other factors that might affect the result, and confuse the picture we are getting from these results10. It is important to have some confounding variables in an experiment11. It is important to try and control as many confounding variables as possible in an experiment

One of the main aims of a scientific study is to generalize from samples. A biologist may be interested in how a fertilizer affects the growth and properties of beans. They cannot test every field with the fertilizer (or even one field) as this will be too large to investigate closely so they will select a sample from it. The rationale is that if they take a fair enough sample – one that is representative of all of the beans – then we may generalize our results from the sample, with a certain degree of caution, to the entire population.

The target population is all of the members of a group from which your sample is drawn and to which the results of your study are intended to relate. A population may be defined by occupation – e.g. university students, or by a common feature e.g. people who were glasses. It would be almost impossible to test every university student or every person who wears glasses so you need to use a sampling method to obtain the participants for your study from that target population. Opportunity sample is the most common – where you select participants on

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the basis of their availability, although this is not necessarily representative as there is no guarantee that the full range of diversity within the population will be obtained in that sample.

Method Procedure Strengths WeaknessesRandom Every member of the

target audience has an equal chance of being selected – use a random number generator

Representative as the researcher does not control who is chosen can be generalized

Very difficult to do unless the target population is really small

Stratified or quota The sample is a proportional representation of the target population. You break down the target population into its constituent groups and recreate a smaller version e.g. by ethnicity

If done properly this is representative and the results can be generalized

Time consuming and difficult to carry out as you need to have information about the whole target population

Opportunity Participants are selected by whoever is available at the time of the study e.g. if you carried out an experiment on everyone in your class

Quick and easy to carry out, likely to be ethical as the participants will be willing to take part

Not very representative as the sample is likely to be taken from a small section of the community e.g. university students

Volunteer or self-selecting sample

Participants select themselves e.g. participants answer an advertisement in a newspaper

Will have access to a large variety of people who will be motivated to take part, likely to be ethical and participants are keen

May be something unique about volunteers which makes it more difficult to generalize the results

Activity Sampling Techniques

1. What is the target population in the following study?a) A study on primary school teacher’s attitudes towards testing for seven year oldsb) The average digit span for children under 5c) The ability of blind people to sense noticeable differences in touchd) The influence of a new advertising campaign on sales of cat foode) The perceptual ability of kittens reared in the dark

2. Explain the difference between an opportunity and a random sample

3. What are the main factors which influence the size of a sample used in an experiment?

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4. You wish to investigate 6th formers’ attitudes towards the food on sale in the canteen. There are 5 departments in the 6th form and the percentages of students are Psychology 34%; History 16%; English 20%; Maths 15%; ICT 15%

a) How would you select a random sample of 100 students?b) How would you select a volunteer sample of 100 students?c) How would you select a stratified sample of 100 students?d) How would you select a quota sample of 100 students?

5. Which of the follow procedures do you think will produce a group of people who would form a random sample?

a) Picking anyone off the street to answer a questionnaire (Target population: the general public)b) Selecting every fifth home in a street (Target population: the street)c) Sticking a pin in a list of names (Target population: the names on the list)d) Selecting well shuffled slips from a hat containing the names of all Wobbly College students and asking those selected to answer your questionnaire on sexual behaviour (Target population: Wobbly College students)

When researchers carry out studies they should always try to maintain reliability, validity and objectivity in their research.

Reliability

If psychological research can be repeated and the same findings are found again and again it is said to be reliable. This consistent finding refers to overtime and over different people. Repeating a research study to see if the results are reliable is known as replication. Replication plays a major role in standardized instructions as we need exactly the same procedure to follow and experiment and replicate.

There are several ways to ensure reliability:

1. Observer reliabilityThis is concerned with researchers in a study measuring the same thing. E.g. if they are going to measure aggression they have to decide what constitutes aggression. This is why it is important to operationalise your variables.

2. Inter-observer reliabilityThis is where more than one researcher observed the same set of participants. This allows the researchers to be able to measure the extent to which observers agree on the behavior they have observed. Pilot studies can be carried out using videotapes to check reliability of observations.

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3. Split-half methodThis is used to make sure that items on a test or a questionnaire are consistent with each other. It involves splitting a test in half after the data has been collected. The two sets of responses are correlated and if there is a high correlation the test is said to be reliable.

4. Test-re-test methodThis involves establishing if a test is consistent over time. E.g. present participants with an IQ test at different times and the results should be similar.

Validity

This refers to the ability of a test or measurement to measure what it is supposed to measure – e.g. if you wanted to see how intelligent someone was you would not count how many sit-ups they could do as sit-ups are not a valid measure of intelligence. Also a questionnaire designed to see how parents treat their children might instead measure what parents think they ought to do if they instead give ‘socially desirable’ responses. There are various types of validity:

1. Ecological validityIt has been argued that no laboratory experiment can be valid since the researcher is not studying natural behavior in a natural setting. Hence the more natural the environment the more ecologically valid the study is.

2. Face ValidityThe degree to which a test/measurement appears to be an example of the behavior of interest e.g. a study of aggression in children – hitting and kicking are high in face validity whereas sarcasm is not. It also can apply to a theory – in the sense that if a theory sounds plausible, it has face validity.

3. Concurrent ValidityThis is where researchers obtain two sets of scores at the same time – one from a new procedure with unknown validity and the other from an alternative procedure or experiment or test for which validity has been established (e.g. you could compare a new method of diagnosing depression with an already established one). Scores from both tests are correlated – if the correlation is high, validity can be inferred.

4. Predictive validityThis is the ability of a test/ questionnaire to predict future behavior/ performance in the future – e.g. the ability of GCSE results to predict A’Level performance.

5. Construct ValidityThe ability of a test to accurately measure an underlying psychological construct (constructed from the mind) eg. Do IQ tests measure IQ?

REMEMBER:

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Reliability = Consistency

Validity = Does it measure what it is supposed to measure

In psychology there are two main different types of data psychologists gather, quantitative and qualitative.

Quantitative data is data which is measured on some numerical basis, e.g. the number of words a person recalls out of twenty or a score on a personality test.

Qualitative data and research emphasizes meaning, experiences (often verbally described), descriptions and so on. Raw data will be exactly what a person has said, or a neutral description of what has been observed. This data can later be quantified to some extent e.g. counting how many times a person has said a positive statement about themselves and how many times negative – but this is not true qualitative data as the interpretation of something as positive or negative is subjective.

Qualitative data Quantitative dataDescription Data in the form of words

Rich detailed data (think quality) The researcher themselves gathers

the data, usually through unstructured interviews or structured open-ended interviews or questionnaires

This is usually used in the early stages of a study

Subjective - individuals’ interpretation of events is important

Data in the form of numbers Precise measured data (think

quanitity) The researcher uses tools such as a

structured closed questionnaire or equipment to gather numerical data

This is usually used in the later stages of research when the researcher knows exactly what they are looking for

Objective – seeks precise measurement & analysis of concepts

Strengths Detailed, rich in depth data is produced – this makes it easier to arrive to more meaningful conclusions which increases the validity of the findings

It is easy to analyse as averages can be calculated and put into tables which is easier than generating themes in qualitative research

It is possible to analysis data to draw comparisons between groups and to draw conclusions about the thing in question

Researcher tends to remain objectively separated from the subject matter, this makes the data more reliable as two researchers will get the same results when analyzing the data

Weaknesses Qualitative data is time consuming to The reduction of thoughts and

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gather and analysis and the subjectivity of the analysis makes it more difficult to generalize the results found

Due to the subjective nature of the research it is unreliable – different researchers may come to different conclusions when analyzing the data

It is difficult to draw comparisons between groups or arrive at a reliable conclusion about a specific thing

feelings to numbers gives a very superficial view of the behaviour being researched, which may lack validity

Quantitative data is more efficient, able to test hypotheses, but may miss detail

In summary: Relative values of quantitative and qualitative methods

Qualitative Methods and Data Quantitative Methods and DataRich Information NarrowSubjective Interpretation ObjectiveRealistic Setting ArtificialSemi-on non-structured Design Highly structuredHigh Realism LowLow Reliability High

Primary Data Secondary Data Original data collected by those who witnessed

the event first hand or carried out an experiment and collected the data themselves

It can be qualitative or quantitative Observed aggression levels in a playground is an

example of primary data An example of a study from Clinical Psychology

which uses primary data is Rosenhan – he noted whether the pseudo-patients were admitted to the psychiatric hospital. The researchers also noted who they were treated by staff once they had been admitted

This is second-hand analysis of pre-existing primary data

The data can be analysed in a different way or used to answer a different question than that used in the primary research

Secondary data usually comments, evaluates and or analyses primary data

Sometimes secondary data is gathered before primary data – at the beginning of a study the researchers may want to gather all relevant secondary data on the topic in order to develop their hypotheses

An example of a study in Clinical Psychology which uses secondary data is Goldstein 1988 – she analysed data already held on

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schizophrenic patients to see whether females differed in their experience of the disorder to males

EvaluationStrengths

In general, primary data is reliable because the researcher can adopt controls and the procedures can be replicated to see whether similar results are found

It is more likely to be up-to-date than secondary data which could have been gathered years before

It is more likely to gather credibility and respect from others as it is founded on authentic evidence and empirical data

Weaknesses Researchers may be subjective in which data they

decide to collect so that it is more likely to ‘fit’ their hypotheses

It is costly and time-consuming as the data has to be gathered from scratch using a large population

EvaluationStrengths

It saves time and expense that is involved when collecting secondary data

In some cases, secondary data is the only way to examine trends in the past

Weaknesses The researcher cannot personally check the

data so its reliability can be questionable Because they did not gather the data the

researcher cannot always be sure that appropriate controls were taken and therefore how accurate the data is

The data may be out-of-date and therefore not suitable for the research

Levels of Measurement:

This refers to how the dependent variable is measured

There are three main levels of measurement:-

Nominal Data - Categories are recorded, such as 'yes/no' answers or gender (male/female)

e.g. What type of pet do you own?

Ordinal Data - Ranked data, such as when someone rates something on a scale.

E.g. most to least attractive Most Least

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Interval/Ratio Data - Data where there is a real measurement, such as inches, grams or seconds etc... Also some scores on IQ tests and personality tests are treated as interval data. Ratio data is the same as Interval but with an absolute zero e.g. heart rate or breathing rate.

(See the next page for more information)

You need to know your levels of measurement and also be able to identify the design of a study in order to decide which statistical test to choose.

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Activity Levels of Measurement

1. When judges give their marks on strictly come dancing at what level of measurement is it safest to treat their data?

2. A set of surgical records classifies patients as ‘chronic’, ‘acute’ or ‘not yet classified’. What level of measurement is being used?3. At what level are the measurements (a,b,c and d) in the table below?

a b c dPremiership Position Points Area (1=London,

2= Northern,3= Southern)

Popularity rating

ArsenalManchester CityNewcastleChelseaEvertonLiverpoolSouthamptonWest Ham

12345678

5650484545423939

12212231

18345267

4. Your sister argues that since she came top in each of the three Maths tests held in her class this year, she must be far better than all the other pupils. What might you point out to her (if you dare)?

5. Think of three ways to measure driving ability, one using nominal level data, one ordinal and one interval.

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6. Below are several methods for measuring dependent variables. For each method decide what level of measurement is being used. Remember human judgements are better treated as ordinal data.

a) People are interviewed on the street and on the basis of their replies are recorded as: pro-hanging, undecided or anti-hanging.

b) Participants’ estimates of various line lengths

c) Time taken to sort cards into categories

d) People choice of The Sun, The Times or The Guardian

e) Participants’ sense of self-worth, estimated on a scale of 1-10

Descriptive statistics are used to summarise the raw data from a study. It can be done numerically – using measures of central tendency and spread or pictorially using graphs.

The aim of descriptive statistics is to give an accurate summary of the data The wrong choice of statistic gives a distorted picture of the data This can lead to the wrong conclusions being drawn from the data

1. Measures of Central Tendency Gives a typical value for the data set Tells you where the middle of the data set is

A) The Mode Simplest measure of central tendency Usually used with nominal data Mode is the most common score in a date set (Mode= Most) If two scores are equally represented then the distribution of scores is bi-modal, three, the distribution is

tri-modal To calculate the mode a frequency table can be drawn up

Advantages It is the most suitable descriptive statistic for nominal data It is unaffected by rogue or anomalous results

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Disadvantages For many data sets there is no modal value or there may be several It does not tell you about every value in a data set

B) The Median The middle score of a data set when data is ranked from smallest to largest value – if there is an odd

number of values simply pick the middle number, if there is an even number of values in a data set find the middle two values and work out their mean.

(Median = Middle) or the central value in a data set Can be used for ordinal, interval or ratio data, most commonly used with ordinal

Advantages Not skewed by outlying scores (rogue or anomalous results) as it is based on the order of the data, not

their actual value

Disadvantages The median does not take all scores into account and therefore is less sensitive to variations in the data If you only have a small amount of data the median becomes meaningless

C) The Mean Often called the average The mean should only be used with interval or ratio data It is calculated by adding together each individual score and dividing this amount by the total number of

scores

Advantages As it takes into account each individual score it is the most sensitive measure of central tendency It can be used as the starting point for inferential statistics

Disadvantages The mean can be artificially raised or lowered by an extreme value or skewed data It can sometimes through up meaningless values – e.g. the average number of children in a British

household is 2.4 (how can you have 0.4 of a child?).

Activities Measures of Central Tendency

1. Find the mode for the following sets of data:

2 4 6 7 7 7 10 12 Mode = _______________

5 19 8 5 6 7 14 5 Mode = _______________

2. Find the median for the following sets of data:

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10 16 22 14 9 5 18 Median = ______________

5 7 3 5 9 3 1 4 Median = ______________

3. Find the mean for the following sets of data:

5 2 4 5 9 7 10 7 Mean = ________________

13 19 20 10 9 14 14 Mean = ________________

Measure of dispersion tell us how spread out the data set is

The Range

This tells us the distance between the Lowest and Highest values in a data set. You calculate it by taking away the lowest value from the highest value and add 1.

Advantages Includes extreme values (these are taken into account) Easy to calculate

Disadvantages It can be distorted by extreme values and therefore be misleading It does not tell us whether the values are closely grouped around the mean or more spread out so it is

unrepresentative of the distribution of values between the extremes

Find the Range for the following data sets:

7 8 1 20 4 16 10 9 Range = ______________

23 54 19 35 23 74 12 47 Range = ______________

Standard deviation

You use the standard deviation alongside the mean as it tells you how much the scores in your data set vary from the mean. The larger the number, the more the data varies.

Advantages It takes into account all values in a data set It is the most sensitive measure of dispersion

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Disadvantages It is distorted by extreme values It is difficult to calculate without a scientific calculator

Probability and Significance

Inferential tests such as Spearman’s rank are used to test the likelihood your results could occur by chance.

Probability = the likelihood of something happening by chance.

The main reason to use statements of probability together with statistical tests is to answer…“…are the experimental results due to chance?”

It is necessary to specify numerically the element of luck that may be involved when testing a hypothesis In psychology probability is represented by use of a p-value of between 0 and 1. A p-value of 1 would be a complete influence of chance, a p-value of 0 would be no influence of chance In psychology p<0.05 is used. This means that there is a one-in-twenty, or a 5% probability that the results

were due to chance This allows you to be confident that the results are more likely to be due to experimental manipulation than a

chance result The results of a psychological study are described in terms of their significance – this does not refer to how

important the experiment is, it refers to the outcome of the statistical analysis of the data Again the lowest level of confidence is one-in-twenty or a 0.05 level of significance, this determines whether

you can accept or reject the null hypothesis

You need to know your levels of measurement and also be able to identify the design of a study in order to decide which statistical test to choose. You therefore need to memorise the following table:

How to Choose a Statistical Test

Research Design

Level of measurement

Independent Groups Repeated Measures Correlational

Nominal X2 Binominal Sign Test

Ordinal Mann Whitney Wilcoxon Spearman’s rank

Interval Unrelated T-Test Related T-Test Pearson’s Product Moment Correlation coefficient

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The shaded area indicate that in this case the calculated value (the number produced from carrying out the statistical test) needs to be lower than the critical value (the value in the statistical table) to be significant. You can remember this because the shaded area produces a backwards L (for lower). For the other tests it needs to be higher.

Activity: Inferential Statistics and Significance

1. What do we mean when something is significant at 0.05?

2. Indicate the significance levels for the following values of T for the Wilcoxon test

a) T=19, N=14, One-tailedb) T=30, N=18, Two-tailedc) T=15, N=15, Two-tailedd) T=31, N=17, One-tailed

3. Indicate the significance levels for the following values of x2

a) x2=10.5, df=3, Two-tailedb) x2=21.0, df=8, Two-tailedc) x2=28.7, df=18, Two-tailedd) x2=35.4, df=26, Two-tailed

Consento Researchers should always obtain participants consent before carrying out any study on them.

Observational studies should only take occur in places where people would expect to be seen by strangers, unless informed consent is received It is difficult to gain informed consent from the following: Adults with learning and communication difficulties, children under 16, prisoners and psychiatric patients. To gain informed consent from participants they should be presented with a brief, detailing the general purpose of the experiment.

Confidentialityo Psychologists should maintain the confidentiality of their participants and the data they collect

from them. Participants’ identities should not be revealed, except with their expressed permission. To maintain confidentiality psychologists should use participant numbers and ensure other identifying characteristics such as handwriting are disguised. In some studies participants sell their stories (Zimbardo’s) but this is ok. In cases where maintaining confidentiality may result in the harm of others, confidentiality can be broken.

Debriefing

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o Participants should be given an explanation about the study they took part in so that they understand fully the reasons for the research. The debrief is used to reassure participants and return them to the state they were in prior to participation. E.g. Milgram fully debriefed all participants and introduced them to Mr. Wallace.

The Right to Withdrawo Participants have the right to withdraw from an investigation at any time, without any penalty.

You can withdraw your consent retrospectively and have your data destroyed.

Deceptiono Psychologists should avoid deceiving participants wherever possible. However, there are

sometimes problems with this e.g. Milgram, and some memory experiments

Protection of Participantso Participants must be kept safe from harm and psychologists should ask participants about any

medical conditions or problems that might put them at risk. Milgram was criticised for causing his participants distress.

Giving Adviceo You should not give participants advice unless qualified to do so. For example if you come across a

psychological or physical problem with a participant they are not aware of you should not give them advice yourself, but refer them to a specialist

Rightso Respect the rights and dignity of participants at all times, for example you must tale into account

cultural differences

DD CC WARP

Debrief

Deception

Consent

Confidentiality

Withdrawal

Advice

Respect

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Use this mnemonic to help you remember the ethical guidelines

Key animal studies:Harlow and Zimmerman – attachmentCalhoun – aggression/ crowding behaviourSkinner – Punishment in rats

Protection

95% of animal research in psychology is conducted on rats, mice and birds (Viney et al 1990)

Why choose animals? The case for animal research To understand natural principles e.g. learning – animals are less complex than humans and results can be

generalised. Procedures cannot always be carried out ethically on humans Animals can have fascinating phenomena e.g. Bat sonar, bee dances We can have maximum control over animals when studying them Some animals reproduce and develop over a shorter period than humans – it is therefore easier to

compare generations

GRAY 1991 – claims that if we can alleviate human suffering by inflicting pain and suffering on animals then we are morally obliged to do soSINGER 1991 – claims the above argument is speciesist (forcing ones species over others) and says this is unjustifiable. He also argues that ethical and moral choices cannot be separated; if we accept that causing pain is wrong, this must guide our moral choice. Therefore no advance in scientific knowledge justifies any amount of suffering.

The case against animal research Practical grounds – can findings really be generalised? Some would suggest humans are unique and

qualitatively different to animals (others argue against this). Animals cannot readily communicate their responses. In addition studies are often carried out in labs and lab animals behave very differently to wild animals

Ethical grounds – benefits to society must outweigh the cost, in terms of pain and distress suffered by the animal

Animals (Scientific Procedures) Act 1986 (the first revision since 1876!) Licences must be gained from the Home Office – the licence covers three aspects

1. Procedures – weigh up pros and cons of research2. Animals – breeding, supply and daily and veterinary care3. Premises – checked by HMIs

BPS Ethical guidelines Respect the law (abide by legislation) Know your species – e.g. different animals have different pain thresholds, or food requirements etc… Protect your species – do not use endangered animals, except in conservation attempts

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In lab studies use as few animals as possible and use appropriate cages Only use reputable animal suppliers It is illegal to cause harm to animals without a Home Office licence Surgical and pharmacological procedures are illegal without a licence Animals must have adequate post-op care. If suffering is too great it must be killed in a manner suitable

for the species If you are in doubt about the condition of an animal, independent advice must be sought

Batesons model for animal research –quality of research must be high, benefit of research should be certain and animal suffering low for a study to be ethical

Same as when using adults but also:

Parental consent must be gained A child’s consent is not the same as an adults due to comprehension level and vulnerability Researchers should intervene and stop a study if the suspect a child is facing difficulties and assume this is

a child expressing their right to withdraw Children should be permitted to ask questions and be fully informed (unless justifiable deception is

supported by colleagues) All information is confidential Information disclosed by the study that affects a child’s well-being must be referred to an expert who may

then follow this up with parents and/ or other services Incentives such as sweets should not be offered as rewards for participation

Longitudinal StudiesLongitudinal Studies are those that follow one set of participants over time, using research methods such as experiment, survey or observation. The important points about longitudinal studies are that the participants are the same, and that measures are taken over time, so that comparisons can be made. A study can last months or years.

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Evaluation Of Longitudinal StudiesStrengths;

Useful for looking at developmental trends. They are the main way to see how an individual's development affects certain characteristics

They use the same participants, which means that participant variables (variables between the individuals taking part) will not give bias in the results

They are useful for looking at the effect of a treatment (e.g. an education programme) and comparing with a control group.

The researcher will usually have better knowledge of the participants making conclusions made about them more valid

Weaknesses; In practice, it can be difficult to keep all the participants for each of the measures, and people can drop

out. This means the sample can become biased if it systematically excludes certain people (such as those who move house a lot, or those who are shy). Participants dropping out of a study is known as the attrition rate

The researchers may themselves change over time, due to moving on or losing funding. This can affect the study, as relationships with the participants may differ

Participants may become wise to the test and/ or too familiar with the researchers making demand characteristics more likely

The studies are time-comsuming and expensive and there is a long-wait before any results are produced meaning it is difficult to get funding for these studies

Replication is very difficult so studies are hard to test for reliability – e.g. there is a cross-generational problem where comparison of one developmental study with another may be confounded by different general conditions (e.g. war) for one generation

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Cross-sectional Studies

This technique is also used in developmental studies. But unlike longitudinal techniques which study one group of people over a long period of time, cross-sectional studies compare groups of people of different ages. Age is not the only factor for a cross-sectional design, you could compare across occupations, education etc…

Evaluation of Cross-Sectional StudiesStrengths;

Cheap and easier to carry out then longitudinal, they take less time so results can be analysed earlier More ethical than longitudinal as they put less demand on the participants in the study Support for developmental theories can be achieved rapidly It has a low attrition rate as few participants are ‘lost’ during these studies Participants are less likely to become ‘wise’ to the test or build up a relationship with the researchers so

less likely to show demand characteristics The cross-generational problem is avoided (See longitudinal studies)

Weaknesses; They are snapshots that gather data from one moment in time – at some other time the participants may

have responded differently Participants variables are not controlled as different groups of people are used – even with matched pairs

the groups will not be exact matches Changes in the same individuals cannot be observed There is the problem of a cohort effect – if the age difference between the groups studied is large than the

difference found may be the result of different experiences (e.g. change in educational practice) and not

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of e.g. stage of development

In our study we carried out a survey using a questionnaire with open and closed (qualitative and quantitative data). The quantitative data was in the form of a likert scale. Below details what a likert scale is, including evaluation. You should also be prepared to discuss different types of surveys (interviews and questionnaires). Likert Scales:

Used to measure attitude Responses such as ‘strongly agree’ ‘strongly disagree’ Responses given a value and added up to give a total score Should have 10+ questions and roughly equal positive and negative

statementsEvaluation:

Good for measuring attitudes The creation of the scale is subjective It is easy to score

Types of Interviews and Questionnaire Surveys

Name Description EvaluationNon-directive interview The person is free to discuss anything Rich in-depth data, useful in study of one

person. Difficult to replicate so unreliable but valid

Informal interview General topics are explore in depth e.g. prejudice

Detailed information provided on the topic of interest, valid but unreliable

Structured open-ended interview

All interviewees are asked the same open ended questions in the same order

Easy to replicate, more reliable than non-directive but less reliable then closed question. Permits good comparison between questions

Fully structured interview

A standard set of questions asked in a fixed order, there is a restricted number of answers e.g. Yes/No

Allows replication and comparison between people. Is reliable. Quick and easy to collect and analyse data, is less valid

Closed question questionnaire

A standard set of questions asked on paper or computer in a fixed order, there is a restricted number of answers e.g. Yes/No

Allows replication and comparison between people. Is reliable. Quick and easy to collect and analyse data, is less valid

Open question questionnaire

A standard set of open ended questions in the same order on the paper/ computer

Easy to replicate, more reliable than non-directive but less reliable then closed question. Permits good comparison between questions

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Laboratory Experiments: An independent variable is manipulated and a dependent variable is measured. An experimental hypothesis explains what is predicted. The hypothesis is directional or non-directional. There is often an experimental group and a control group. Extraneous variables are controlled for, so there are no confounding variables. A cause and effect relationship is claimed. Behaviour is reduced to a measurable concept by operationalising the IV and DV. Sampling is careful to avoid participant variables. Controls are careful to avoid situational variables. Care is taken to avoid experimenter effects. With a repeated measures design, counterbalancing or randomisation is used to avoid order effects. Tend to gather quantitative data.

Strengths; They tend to be reliable because controls mean they are replicable. They tend to be fairly generalisable because sampling is careful and representative. The data is gathered objectively, usually because someone other than the researcher can often run the

experiment, and also because the IV is tightly controlled and the DV follows - there is then little need for interpretation. It also reduces the change of extraneous variables effecting the outcome of the results.

Weaknesses; They tend not to be ecologically valid because the setting is usually unnatural. They tend not to be valid with regard to the task, because of all the controls. They can lack credibility because of the artificial setting and artificial task. There can be ethical problems because of the controls, and the artificial tasks and setting.

These are studies with an experimental design (they have an IV and DV), which taken place using participants in their natural surroundings. The IV is still mainipulated as in a lab experiment but the setting is realistic and not in a laboratory. Field experiments can therefore be described as contrived, since the researcher creates the levels of the IV. An example of a field study was carried out by Piliavin et al (1969), they wanted to investigate bystander apathy by seeing how many passengers on a subway would help a person who collapses. Piliavin varied the type of person who collapsed and measured how long it would take for a bystander to help. The study was carried out in the natural environment of the participants (the subway) but the experimenter still manipulated the IV (the gender/age of the person that collapsed varied).

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Advantages of Field Experiment:Participants may not be awarethat they are taking part in a pyschological study so their behaviour is probably more realistic and not subject to demand characteristics or experimenter effects. This research method has ecological validity, so the findings can be generalised to real-life situations.

Disadvantages of Field Experiment:The experimenter has no control over the setting, so unexpected or extraneous variables may have an influence on the findings, which threatens the reliability and validity of the study. Furthermore they are generally more time consuming and difficult to set up and there may be ethical problems. If the participants are unaware that they are taking part then they would not have given consent and do not have the right to withdraw from the study. In these cases a researcher may choose to fully debrief them after the study is complete and offer them the right to withdraw their results.

These are studies carried out in real-life settings in which the IV exists already so cannot be controlled or manipulated. These studies have a reasonably high level of ecological validity but its impossible to clearly establish cause and effect, since other factors and changes will also be having an influence. Opportunities for such investigations are rare but Charlton et al (2000) came across an ideal situation on an island called St Helena. They described the effects of the introduction of satellite television in 1995 and were able to compare the behaviour of children prior to tv and several years after. They also made comparisons to children living in London.

Advantages of Natural Experiments:They offer ecological validity because data tends to be collected under natural conditions and, as the IV is naturally occurring, it could be argued that it is more realistic. They may be more ethical because participants are unaware they are taking part in a study per se, as the situation is occurring regardless of the presence of the researchers.

Disadvantages of Natural Experiments:The lack of control over the participants involved in the study and extraneous variables could affect the results. For example, the researchers cannot select which participants take part in the study as they have to use those who are available and in the situation at the time. A natural situation tends to be a unique situation, so can be hard to find and almost impossible to replicate therefore reducing reliability.

Comparing Experiments

Factor Lab Experiment Field Experiment Natural ExperimentEnvironment Artificial Natural NaturalIndependent variable

Controlled Controlled (partly) Natural

Allocation of participants to conditions

Random Random Non-Random

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Control of extraneous variables

Tight Weaker Weaker still

Awareness of aims by participants

Pps (expect very young children) must be aware they are taking part (though not what the design really is)

Pps unaware of study (so cannot guess design, show demand characteristics)

Pps unaware of study (so cannot guess design, show demand characteristics)

Replication Easier Harder Extremely difficultMundane realism Lower Higher Higher stillGeneralisation (external validity)

Often weak to everyday behaviour

To similar settings good, to other settings less good

To similar settings good, to other settings less good

Other disadvantages Setting more likely to create apprehension and wariness of surroundings. Tasks often artificial

Greater likelihood of confounding variables effecting the results

Much more difficult to establish cause and effect

Correlation DesignsFreud's theories are difficult to test, but one way of testing them is to use a correlation design and self-report data. Freud did not use this methodology, but it is useful for testing his ideas. Self-Report Data - The data the participant provides about themselves e.g. a questionnaire. It is usual, when gathering self-report data, to include rating scales – e.g. a likert scale. Rating scales give Ordinal Data.

In a correlation design, it is not suggested that one variable causes the other, just that they are related. In a correlation, it is not a difference between two variables (the IV and DV) that is looked for, but a relationship between them.

Positive & Negative Correlations

Correlation - A relationship between two variables measured on a scale, and where both measures come from one individual.Positive Correlation - Both variables rise, e.g. IQ rises, income rises.Negative Correlation - One variable rises and the other falls, e.g higher the IQ, less likeliness of mental health problems.

Inferential Statistics are statistical tests that can do more than describe the data (e.g. the mean median and mode are called descriptive statistics), they can suggest how strong the difference or relationship is.

Correlational design with ordinal data requires the Spearman's Rank Correlation Coefficient Test (Spearman's Rho). This test relies on the ranking of the scores to see if they co-vary (are related) closely enough to draw firm conclusions. A perfect positive correlation gives a result of +1 and a perfect negative correlation gives a result of -1. No correlation at all

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gives a result of 0. The closer the test result is to 1 (+ or - ), the stronger the correlation.

The Spearman's Test looks at the rankings for the two sets of scores, and carries out a test to see if the ranks for each score for the same person are similar enough or different. If they are similar enough, then it can be said that there is a correlation. A Spearman's Test is carried out if:-

- What is being tested is a relationship, not a difference, between two scores.- The level of measurement is ordinal or interval/ratio.- The type of design is a correlation, meaning the same participant gives both scores.

Evaluation Of Correlation DesignsStrengths;

There is little manipulation of variables. Measures are often taken of existing situations with few controls needed - which can make for a straight forward design. The two measures are taken, and the scores tested to see if there is a relationship. This is quite straight forward compared with some experiments, observations and surveys

Correlations can show relationships that might not be expected, and so can be used to point towards new areas for research

Weaknesses; A relationship is found, but without finding out whether the two variables are causally or chance related.

When looking to build a scientific body of knowledge, it is usual to claim cause and effect relationships between things – you cannot do this with correlational designs

Correlational designs tend to lack validity, because at least one of the variables often has to be operationalised, which tends to make it unnatural. Whenever a score is manufactured, there is always the chance that it is not really measuring anything useful.

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Activity Correlational Designs

In a correlation study you are interested in the relationship between scores on a test of mathematical ability and verbal reasoning.Both are scored out of 100

Participant Mathematical Ability Verbal Reasoning123456789

356773876349526993

408571796545586692

1. Plot the data on a scattergram (remember titles, axes labelled etc..)

2. What type of correlation does it show?

3. Explain the term order effect (remember practise effects are a type of order effect). In conducting this study, how could you control for order effects?

4. What is the major disadvantage of a correlation?

5. Are the following positive or negative correlations?

a. The higher cortical arousal (brain activity), the more introverted a person is

b. The quieter the tube is, the less stressed a person is at work

c. The older you get, the worse your memory gets

d. As the temperature rises, sales of woolly jumpers decreases

e. The more bags you carry, the slower you walk

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Case StudiesCase studies involve studying one unique individual (or small group or particular programme) and gathering in-depth, detailed and rich data about that individual. Within a case study, many research methods are used, such as observations, questionnaires, interviews, experiments and case histories. Case histories gather qualitative data, and find out the story of the individual. As much other data as is suitable and possible is then gathered, to achieve the required depth. Triangulation is used, which means pooling all the data from the various research methods, and looking for common themes and trends.

Freud's Style Of Case StudyFreud used case studies to gather in-depth, detailed data about an individual, and to tis extent he used case studies in a standard way. He used methods such as free association, dream analysis and slips of the tongue to try to uncover unconscious wishes and desires. Freud used his case studies not only as a research method, but also as a therapy, as he used psychoanalysis to help his patients (analysands) to uncover their repressed memories.

Research Methods In Freud's Case Studies One method Freud used was free association, which is where the analysand allows a stream of

consciousness out, and the analyst listens to find connections with the aim of uncovering unconscious wishes

Freud also used dream and symbol analysis. This is where the analysand describes a dream, and the analyst looks for meaning in the dream. The manifest content of the dream is the description of the dream itself, and the latent content of the dream is the underlying unconscious thoughts that are revealed through the manifest content by analysis of symbols. The analyst interprets the symbols to find the latent content.

A third method used by Freud is analysis of slips of the tongue, which is where the analysand uses the wrong word for something. Freud thought these mistakes revealed unconscious desires. Much of Freud's analysis of symbols consists of sexual analysis

Evaluation Of Case StudiesStrengths;

Useful, because they are often the only way of studying a particular phenomenon They can gather data that cannot be obtained by other means Case studies give psychological researchers

the possibility to investigate cases, which could not possibly be engineered in research laboratories. For example, the Money Case Study

Produce valid data - data comes fairly directly from the people concerned, and is usually gathered in their natural surroundings

Weaknesses; Not replicable because the situation is unique - cannot be tested for reliability. It is hard to use the results and say they are true of other situations. This concerns generalisability - if

results come from one unique individual or small group, the findings cannot be generalised. They can suffer from researcher bias, Freud has been criticised for producing case studies in which the

information was sometimes distorted to fit the particular theories about behaviour (e.g. Little Hans). This

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is also true of Money’s interpretation of the Bruce/Brenda case study when he ignored evidence that went against his theory.

Evaluation Of Freud's Case StudiesStrengths;

They can be used to help the patient as well as to gather data. They are therapeutic, and have a practical application

They use special means to uncover unconscious thoughts that cannot otherwise be accessed, and Freud had to develop special ways of gathering data from such a complex situation

Weaknesses; The analyst has to do a lot of interpretation so could be subjective, whereas scientific study requires

objectivity The concepts, such as the unconscious, are not measurable, and so are hard to test in a scientific way. This

means that conclusions might be drawn, but there can never really be any proof

Freud's Case Studies & CredibilityFreud's work has been criticised for being incredible - literally unbelievable. His explanations for neuroses were based very strongly on interpretations of unconscious desires, and he saw these as sexual. Many people do not find his ideas credible - for example the idea that around five years old a boy has a sexual desire for his mother and a fear of his father (The Oedipus Complex).

Masson (1989) went further, and criticised psychoanalysis in three ways:-

- The interpretation of the analyst can push the patient towards certain values and goals that may not be their own, so there is an issue of the power of the analyst over the analysand- There is gender bias in Freud's work. For example, boys are focused on more than girls - girls are held to have a less strong identification, and so weaker moral development- There is undue emphasis on sexual matters, particularly where transference occurs, which is about the patient having feelings for the analyst. This is ethically very sensitive

1. Comparing MZ and DZ twins. This looks at comparing MZ’s and DZ’s who share the same environment. If MZ’s (who share all their genes) are more similar this provides support for the influence of genetics (or

nature) Gottesman (1991) looked at the concordance rates for MZ’s and DZ’s for schizophrenia (concordance

means the probability of both having the disorder). He found that MZ = 48% and DZ = 17%. This result demonstrates the importance of genes, but also highlights that genetics is not the only factor in Schizophrenia as the concordance rate for MZ is not 100% suggesting an environmental influence also.

2. Comparing MZ twins which have been separated. MZ twins reared apart show more differences than those reared together – this highlights the importance

of nurture37

However, MZ twins reared apart are still much more alike than two unrelated people. This demonstrates the importance of nature

Loehlin (1992) compared the personality types of MZ twins reared together and apart using a correlation design. He found that for extraversion MZs reared together had a correlation of 0.51 whereas those reared apart had 0.38. This shows that environment plays a factor in personality development but so does genes.

EVALUATION:

A lot of evidence supports the role of genes in intelligence, personality etc… Other evidence (Hetterna et al. 2003) suggests that MZs are more similar than DZs in their tendency to have a fear classically conditioned. It is assumed when comparing MZ and DZ who have been reared together than they share the same environment, however, as MZs are identical their parents and others may have been more likely to treat them in exactly the same way thus making their environment more similar. There is only a small amount of research that has been carried out on separated twins. In addition, the studies vary upon the ages in which the twins were separated, and also in the amount of time the twins had spent together after being reunited but before taking part in the research. They may have also experienced a similar environment during separation. The importance of genetic factors may have been underestimated due to the fact that MZ twins do not always share the same environment before birth. Some MZs share the same placenta (known as monochorionic or MC) whereas others do not (dichorionic or DC). Davies et al (1995) looked at the concordance for MZ MC twins and MZ DC twins for schizophrenia. He found for MC it was 60% but for DC 10.7%.

This involves comparing children who have been adopted for similarities between their adoptive parents and birth parents.

Similarities between a child and their adoptive parents supports the influence of nurture Similarities between a child and their biological parents supports the influence of nature Heston (1966) compared 47 adults who had been adopted as children because their mothers were

schizophrenic with 47 adoptees whose parents were not schizophrenic he found that 10% of the adopted children whose mothers had schizophrenia had also gone on to develop schizophrenia compared to none of the controls

EVALUATION:

This is the best method available for comparing the influence of genes an environment. They are especially useful if adoption has occurred at birth as this can rule out hereditary influences. Adopted children are a minority therefore there are problems associated with generalising these results to the rest of the population.

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Children who have been adopted are often placed in similar environments to those of their biological parents.

Laboratory Animal Learning Studies: Ethical issues concerning use of animals must be adhered to, such as suitable caging, use of anaesthetics,

not using endangered species, not causing unnecessary pain and suffering, having a licence when required, using as few animals as possible, always looking for an alternative first.

Studies must pay attention to features of the species used, so that conclusions are appropriate given the natural tendencies of different species.

Generalising from animal studies to humans is problematic - to the point where animal studies may not be useful.

Findings from animal studies can benefit animals with regard to their care - though this may not be a strong enough argument for their use.

One way that psychologists study human behaviour and the biological influences on it is by using brain scanning techniques this allows the brain to be closely examined. Before brain scans that penetrate the skin and bone were introduced, the only way available to study the brain was to operate on people or look at the brains of corpses.Magnetic Resonance Imaging scans is a way of seeing a picture of the brain inside the skull, just like an x-ray. It allows us to see the structure of the brain and therefore whether there is damage or tumours that may need treatment. During an MRI sca, the patient is placed in a large scanner which passes a very strong magnetic field through their head. The nuclei of some atoms in certain molecules spin in a particular way when they are placed in a magnet, which allows a detailed picture of the brain to be produced on a computer. In the scanner, electromagnetic waves are passed through the body by the magnet, and the nuclei in hydrogen molecules emit their own radio wavew at a frequency that the scanner picks up. Because hydrogen concentrations vary in different areas of the brain, a very detailed image of the brain at cross-sections can be seen.

Positron Emission Tomography scans are ways of seeing a picture of a ‘working’ brain. It can also show any malfunction, therefore helping to identify damage or tumours. Patients are injected with glucose or water that has been labelled with a radioactive tracer while they lie with their head inside the scanner. Once the substance reaches the brain, the brain cells start to uptake the oxygen in the water or glucose and the traces begins to decay. When the tracer decays it emits positrons, and the more glucose or oxygen the cells in the brain use up, the more positrons there will be emitted, they collide with electrons and form gamma rays which are detected by the scanner to produce an image of the activity in areas of the brain.The use of the above scans within psychology, have proven to be an objective and reliable method of research and are not open to experimenter bias.

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Observation:Sometimes, the behaviour to be observed is carried out in a structured setting, where observation can be by using a one-way mirror or screen. Apparatus is available, and a structure for the behaviour is laid down. This is usually in situations such as childcare, or observations of other relationships. These are called structured observations. Most observations are naturalistic, because natural behaviour is what is required.

Naturalistic Observations - Take place in the participants' natural setting.

Non-Participant Observations - The observer is not part of the situation.

Participant Observations - The observer is also a participant.

Observations can be;-

Overt - The participants know that they are being observed and possibly why.Covert - The observation is kept secret from the participants.

Observations usually include tallying. Tallying produces quantitative data, whereas if observations include writing down quotes or telling the story of what is happening, that is qualitative data.

Evaluation Of Observation As A Research Method

Strutured ObservationsStrengths;

Structured observations can be useful because there are controls, which means that cause and effect conclusions are more easily drawn, as there are fewer factors to affect what is observed.

Such observations can be tested for reliability, as they are replicable.

Weaknesses; Structured observations can lack validity, as there is a baseline expectancy for behaviour.

Naturalistic ObservationsStrengths;

They take place in a natural setting, and the observations are of naturally-occurring behaviour.

Weaknesses; May be seen as not very reliable because they take place in the participants' natural setting, which is hard

to replicate. Behaviour at one moment in time is not likely to be repeated. However, if the procedure of the observation is fully documented, another researcher could repeat it, and it might be found reliable. The more controlled the observation, the more likely it will be found to be reliable.

Overt ObservationsStrengths;

Informed consent can be obtained, and the right to withdraw can be given.

Weaknesses;

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Might lead to unnatural behaviour, simply because the participants know that they are being watched.

Covert ObservationsStrengths;

The participants do not know that they are being studied. Their behaviour should therefore be as usual, which makes it valid behaviour.

Weaknesses; Less ethical because the participants are not aware that the study is taking place, therefore, have not

given consent to be observed, and do not have the right to withdraw from the study.

Non-Participant ObservationsStrengths;

The observer can concentrate on time sampling and tallying, which is hard to do if you are also trying to take part in the group or behaviour.

Weaknesses; Can lack validity because the observer affects behaviour.

Participant ObservationsStrengths;

Valid because there is no 'strange' observer affecting behaviour. The observer is already part of the group.

Weaknesses; Difficult - There is no time to make notes or actually observe. If you are a participant it may be hard to step back and watch. On the other hand, the participant

observer has shared understanding with the group, and so understands the data in a way that a non-participant observer might miss.

Used to analyse a variety of media e.g. newspapers, TV It involves, deciding upon a specific research question, choosing a sampling strategy, choosing a recording

unit, testing the coding on sample material to test reliability, conducting the content analysisEvaluation:

It is unobtrusive As the documents are permanent it is easy for the materials to be used by other researchers and be

tested for reliability It is a quick and easy way of conducting longitudinal research It is hard to judge cause and effect – are the materials a reflection or a cause of the world we live in The analysis can be very subjective unless you conduct strict inter-rater reliability tests

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Cross-cultural research is carried out to see if behaviour is universal. For example we have found that language development occurs in the same stages in most cultures – all babies coo before they adopt a language and dialect and all make grammactical errors at a similar age. The stages of language development are therefore robust and universal.

Cross-cultural research can also give us important psychological insight into whether behaviour is due to nature or nurture. If behaviours differ across culture we can assume it is due to socialization (nurture) and not biology (nature).

Evaluation Ethnocentrism may occur because a researcher may interpret the findings of a study in terms of their own

beliefs. However, others would argue that cross-cultural research discourages ethnocentrism because the research is not too confined to one culture

Cross-cultural research can be used to ensure the reliability of research findings, because if the same conclusions can be drawn in different cultures it is said to be reliable and universal

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