Psychological Science

How psychological research is done.

Curiosity, skepticism, humility

Psychology, like all science, uses scientific method to construct theories that organize observations and apply testable hypothesis.

Can’t rely on common sense.

Limits of intuition Hindsight bias: We tend to believe, after learning an outcome, that we

would have foreseen it all along. “I knew it all along” phenomenon Finding out that something has happened makes it seem inevitable.

Overconfidence: We tend to think we know more that we do.

Critical thinking Involves thinking that

does not blindly accept arguments and conclusions. Examines assumptions Explores hidden

values Evaluates evidence Assesses conclusions Ask questions!

Scientific method

Step 1: Theory; an explanation that organizes and links observable facts. Must imply testable

predictions (Hypothesis). Step 2: Hypothesis, A

testable prediction, often implied by a theory.

Scientific method Step 3: Design Research An

“ordeal of proof” for the hypothesis.

Operational Definitions: A statement of the exact

procedures used in a study. Allows a study to be replicated. That is, to repeat the study with

other participants or circumstances to see if the theory hold true.

Scientific method

Step 4: Observation Gather objective data from

direct observation Step 5: Analyze and

Refine Run statistical analysis of

the data Refine theory if necessary

Ideally will go on to publish, receive criticism and replicate results

Research Method #1: Descriptive Psychologists describe

behavior using the: Case study Survey Naturalistic Observation

Remember, these methods describe behavior, they do not explain it.

The Case Study Examination of one

individual or small group in great depth, hoping to reveal truths about all of us. One of oldest methods Can include interviews,

observations, and test scores.

Frequently used by clinical psychologists.

Case Studies A detailed picture

of one or a few subjects.

Tells us a great story…but is just descriptive research.

Does not even give us correlation data.

The ideal case study is John and Kate. Really interesting, but what does it tell us about families in general?

The Survey Population: all cases in a

group from which samples are drawn from a study. That is, the whole group you

want to study and describe. Random Sample: A sample

that fairly represents a population because each member has an equal chance of being included. Makes sure the group studied

represents the targeted population.

Survey Method•Most common type of study in psychology

•Measures correlation

•Cheap and fast

•Need a good random sample

•Low-response rate

The Survey Ask people to report

their own behavior, thoughts and attitudes.

uses questionnaires or interviews.

Participants must be representative of the larger population. Best achieved by

random sampling.

Naturalistic Observation Watching and recording

the behavior of organisms in their natural environment. Such descriptions can be

very revealing, such as tool-using chimps.

No variables are manipulated.

Often used to generate ideas for other research.

Naturalistic Observation Watch subjects in their

natural environment. Do not manipulate the

environment. Illuminate human

behavior The bad is that we can

never really show cause and effect.

Correlational Method Correlation expresses a

relationship between two variables.

Does not show causation.

As more ice cream is eaten, more people are murdered.

Does ice cream cause murder, or murder cause people to eat ice cream?

Types of CorrelationPositive Correlation The variables go in

the SAME direction.

Negative Correlation The variables go in

opposite directions.Studying and grades hopefully has a positive correlation.

Drug use and grades probably has a negative correlation.

Correlation Coefficient A number that

measures the strength of a relationship.

Range is from -1 to +1

The relationship gets weaker the closer you get to zero.

Which is a stronger correlation?

-.13 or +.38 -.72 or +.59 -.91 or +.04

Overgeneralization False Consensus

Effect The tendency to

overestimate how much others share our own beliefs and behaviors.

To avoid our tendency to over-generalize we must use random sampling.

Research Method #2: Correlational Correlation coefficient: A

statistical measure used to describe the strength of a relationship between two factors. How they will change

(vary) together. How they predict one

another.

Correlations Negative correlation: inverse relationship

between two variables Coefficient up to -1.0

Weak correlation: little or no relationship between two variables. Coefficient is near zero

Positive correlation: one variable increases or decreases in direct proportion to the other. Coefficient up to +1.0

Correlation Coefficient

Correlation coefficient

Indicates directionof relationship

(positive or negative)

Indicates strengthof relationship(0.00 to 1.00)

r = +.37

Scatter Plot A graph with dots,

each dot representing the relationship between two variables. The slope of the dots

suggests the relationship of the variables.

The amount of scatter suggests the strength of the correlation.

Scatter Plots

Perfect positivecorrelation (+1.00)

No relationship (0.00) Perfect negativecorrelation (-1.00)

September 23, 2013 Objectives: To develop an understanding

of correlation, mean, median, and mode.

Do Now: Give an example of a positive correlation

that you have experienced or witnessed.

Correlation Coefficient The correlation coefficient

tells us nothing about cause and effect. However, it can help us see

things more clearly. That is, see relationships that may not be readily visible to us.

Shows us the actual extent to which two things relate.

Remember: Correlation does not prove causation (only its possibility)!

Illusory Correlation When we see a

relationship that does not exist. We will often notice and

recall events that confirm this belief.

Especially true in regards to unlikely or dramatic events.

We search for order in random events.

Research Method #3: Experimentation

Best way to uncover cause and effect; test hypotheses. Can manipulate factors of

interest. Or, hold constant (control)

other factors.

Random assignment is an important factor.

Variables Independent variables (IV): the

variable that is manipulated. The one whose effect is being

studied. Dependent variable (DV): the

behavior or mental process that is being measured.

It may change in response to changes in the independent variable.

If the DV changes when only the IV is changes, researchers can conclude the change in IV caused the change in the DV.

If… Then… Use an “if…then..”

statement to determine the independent and dependent variables.

What follows the “if” is the independent variable (or cause.)

What follows the “then” if the dependent variable (or effect.)

Eating cookies before class each day will lead to higher average scores.

Variables:Independent (IV)

Controlled by experimenterThe “cause” variable

Dependent (DV)Dependent (DV)Predicted by experimenterPredicted by experimenterThe “effect” variableThe “effect” variable

Between-Subjects design Subjects are randomly

assigned to different experimental groups. Those receiving treatment are the

experimental condition. Those not receiving treatment are

the control condition. They are the comparison group.

Between-Subjects design: because the participants in the experimental and control groups are different individuals.

Confounding Variables Differences between the

experimental group and the control group other than those resulting from the independent variable. May include experimenter

bias or demand characteristics.

Random assignment of participants to either control or experimental groups minimizes the existence of preexisting differences.

Random SamplingTo select participants from populationAllows you generalize results

Random AssignmentTo divide participants into groupsControls confounding variables

Experimenter Bias Experimenter Bias: when

the researchers expectations or preferences about the outcome influence the results obtained. For example: Can be unaware

he or she is treating either the experimental group or control group differently from the other.

A smile to one group

Demand Characteristics Clues participants

discover about the purpose of a study. Includes rumors they hear

about how they should respond.

Single-blind procedures help with this. The participant does not

know which group they belong to - experimental or control.

Double-blind procedure To eliminate both

experimenter bias and demand characteristics, experimenters use the double-blind procedure: Neither the research staff

nor participants know the treatment participants have received.

Often used in drug trials.

Placebo effect In drug experiments, the

experimental group receives the active drug. The control group receives a

placebo, or drug which seems identical, but lacks the active ingredient.

Placebo Effect: experimental results are caused by expectations alone. Thinking you are getting

treatment can help you improve.

Within-subjects design A research design that uses each

participant as his or her own control. For example; comparing participants

behavior before receiving treatment to her behavior after receiving treatment.

Counterbalancing: When two treatments are used half the subjects get one first, the other subjects get the other treatment first. Determines if the order of the

treatments cause an effect.

Statistical Reasoning Range: Difference

between the highest and lowest score.

Standard Deviation: How much scores vary around the mean.

Statistical significance: how likely it is that a result occurred by chance.

Measures of central tendencies Mode: The most

frequently occurring score.

Mean: The average Add all scores and

divide by total number of scores.

Median: The middle score. Half are below and

half are above.

Let’s do an experiment. Hypothesis: The red pill will reduce anxiety. We operationalize the definition of anxiety

to mean those whose doctors claim they suffer from anxiety.

We find 100 people who fit the operationalized definition

We randomly assign half the men to the experimental group and half the men to the control group. (Same with women).

I, the researcher, do not know which group will receive the medication and which will receive the placebo. That means this is a double-blind experiment. This will reduce experimenter bias.

The experimental group will receive the actual medication. The medication is called the independent variable.

The control group will receive a sugar pill (the placebo).

The research team will ask all participants to measure their level of anxiety on a scale from 1 to 10. Anxiety is the dependent variable (what is measured).

The control group will usually report a decrease in anxiety even though they received no medicine. This is called the placebo effect.

Now that the experiment phase is done, you must consider the confounding variables. This is the stuff that will screw up your experiment. Ex: what if the control group had a mean age much less than the experimental group? What if the 2 groups had a different percentage of women?

Our original hypothesis was: the red pill will reduce anxiety by 40%.

Results: The experimental group reported a mean of 10% reduction in anxiety versus a 5% reduction for the control group.

Theory: After several replications, the medicine has no significant effect on anxiety.

Reliability and validity? A finding is reliable if it can be replicated. If

subsequent studies show that the red pill reduces anxiety then the findings are reliable, thus supporting the hypothesis.

A study is valid if it measures what it is supposed to measure. If our experiment measured hypertension instead of anxiety, then the test is invalid, even if it is reliable.