week 17 the scientific method lecture lm

Dissertation Preparation (SPO039-2) – Lecture 2

Notes by Lee TaylorThe University of Bedfordshire

Department of Sport and Exercise SciencesContact: [email protected]

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Why are Research Skills important as Sports Scientists / Coaches / Personal Trainers?

• Human knowledge and beliefs are often flawed, unscientific and irrational in their development eg:

- ~50% of the population of the USA do not believe in evolution by natural selection!

- 47% believe in UFOs!

- 49% believe that it is possible for someone to be physically possessed by the devil!

- 26% believe in mental telepathy!

The basis of knowledge•The basis of knowledge in the real world can be

unsubstantiated guesses, hunches, or speculations!—Scientists are not exempt from these personal

beliefs, prejudices, faith, hope, hunches and myths.

Therefore

•To develop new knowledge, as scientists, we must follow guidelines/rules specific to developing new knowledge, aka The Scientific Method!

—The primary aim in following The Scientific Method is to avoid these biases in research – scientists should be as objective as possible.

Take home message of why research methods are important!

• As sport scientists, personal trainers and coaches we need to ensure the theory we use in our practice, whether that be as an educator, coach or trainer, is correct.

— To ensure this is achieved any evidence we use should have been proved / collected / analysed using the guidelines mentioned previously, i.e. The Scientific Method, to reduce biases and anecdotal practises.

Revisit to Scientific Method

What are the two general approaches to research?

1.The scientific method (hypothetico-deductive method)

2. The unscientific approach.5

Unscientific methods are reliant on:

IntuitionCommonsense and gut reactionAuthority Teacher, parent – reliability?TenacityBeliefs, superstitions, no logical foundation

Data

Identify Variables

Measure Variables

• Graph Data• Fit a model

Initial Observation(Research Question)

Generate Theory

Generate Hypotheses

Collect Data to Test Theory

Analyse Data

Discuss the meaning and implications of the findings

The scientific method

Unscientific Method

Could be argued that that all are necessary to some degree to answer specific research questions

The best method?

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Scientific approach

Systematic: Identification and labelling of variables and the design of a test/method to test any relationship between variables.

Logical: Examination of the procedures used in the research process allows researchers to evaluate the conclusions drawn.

Empirical: Researcher collects data on which to base decisions.

Reductive: Researcher uses individual events (data) to establish relationships.

Replicable: Research process recorded to enable others to test the findings (validity and reliability) and use previous results as a basis for future research.

Unscientific approach

Tenacity: An unscientific method of problem solving in which people cling to certain beliefs regardless of the lack of supporting evidence.

Intuition: Common sense or self evident, however, many self-evident truths are subsequently found to be false, e.g. the Earth is flat.

Authority: Reference to some authority, e.g. a teacher / religious leader / renowned academic as a source ok knowledge – their knowledge can be bias/wrong Galileo vs Ptolemy.

The rationalistic method: Knowledge derived by reasoning can be flawed by simple premises e.g.

Basketball players are tall.Tom Thumb is a basketball player.Therefore, Tom Thumb is tall. 7

Data

Identify Variables

Measure Variables


1) Initial Observation(Research Question)

2) Generate Theory

3) Generate Hypotheses

4) Collect Data to Test Theory

5) Analyse Data

6) Discuss the meaning and implications of the findings


6 key stages of the hypothetico-deductive method 8

RQ, Theory and Hypotheses• Research Question: Is a broad question related to a topic of

interest which tentatively indentifies that there may be a relationship among variables

- e.g. Hypoxic training and sea level athletic performance.

• General Theory: A hypothesised general principle or set of principles that explain known findings about a topic and from which new hypotheses can be generated

- e.g. hypoxia effects VO2 max.

• Hypotheses (experimental hypothesis): Are specific predictions, underpinned by previous observations and knowledge which are the “best guess”, “educated guess” or “expected result”

- e.g. VO2 max decreases in hypoxia. 9

1. Initial Observation (research question)• In a nut shell “come up with a question that needs

answering”:

Mini Task 1Using your provisional dissertation topic, write down your broad research question(s). - Explain to the person next to you what you are generally going to investigate.

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1. Initial Observation (research question)• In a nut shell “come up with a question that needs

answering”:

• SES?

• SSPT

• SSC

- Does altitude training improve sea level performance?- Does bicarbonate loading improve repeated sprint performance?

- Do super sets increase muscle mass (hypertrophy/hyperplasia)?- Is static or dynamic core strength training key to reduced lower back pain?

- Does whole body vibration exercise maintain muscle temperature at half time?- Are double sessions twice as effective compared to single sessions in pre-season training?

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1. Initial Observation (research question)• Once you have a broad research question, this needs to be refined:

e.g. why is Usain Bolt the fastest man on the planet?

- Many factors, or variables need to be considered to answer this question:

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for your research questions what factors could be considered?


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e.g. why is Usain Bolt the fastest man on the planet?


GenesTrainingAttitudeEnvironmentBiomechanicsNutrition

It is the considerations of these factors or variables that allow more specific theories to be generated.

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1/2. Initial Observation and theory generationGenes: A predisposition for explosive power and adaptation to training, fibre type distribution, phenotype to avoid injury.

Training: An effective and appropriate regime.

Attitude: Positive, willingness to train, accept criticism.

Environment: Weather (conducive to training) / Coaches/ physios / sponsors

Biomechanics: Long Limbs, perfect gait.

Nutrition: Adequate, well balanced nutrition

From further consideration and greater exploration of these concepts we can now generate specific research questions/theories. 15

1/2. Initial Observation and theory generation

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1/2/3. Initial observation, theory and hypotheses

1. Calvin has an initial observation (1) and research question (2).

2. 1 and 2 ultimately help form his hypotheses (3).

11 2 3

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Data

Identify Variables

Measure Variables



2) Generate Theory



5) Analyse Data



Lets work through stages 1 – 3 with an example18

1/2/3. Initial observation, theory and hypotheses Before we can generate an hypothesis (3) using our RQ (1) and GT (2), we must identify the independent and dependant variables.

Independent Variable (IV): What the researcher is manipulating.

Dependant Variable (DV): Is the effect of the independent variable.

Example:

Research question: The effect of hypoxia (altitude) on an individuals VO2max?

Theory: Hypoxia does effect VO2max.

Hypotheses: Hypoxia will decrease VO2max.

Independent Variable = Hypoxia / normoxia

Dependent Variable = VO2max

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1/2/3. Initial observation, theory and hypotheses Mini Task 2

Using your provisional dissertation topic refine your research question(s), general theory and specific experimental hypothesis(es), ensuring you identify your variables.

Example:

Independent Variable (IV): What the researcher is manipulating.

Dependant Variable (DV): Is the effect of the independent variable.

Research question: The effect of hypoxia (altitude) on an individuals VO2max?

Theory: Hypoxia does effect VO2max.

Hypotheses: Hypoxia will decrease VO2max.

Independent Variable = Hypoxia / normoxia

Dependent Variable = VO2max

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3. Hypotheses generation – guidelines

Remember when generating hypotheses the following processes should have been adhered to:

1) The hypotheses is normally generated by indentifying a research question and then a suitable theory.

2) This process and the resulting hypotheses should be based on a theoretical construct and/or results of a previous study (scientific underpinning – the reading of articles!!!!!!!!!!!).

3) The researcher should identify both the independent and dependant variables.

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Data

Identify Variables

Measure Variables



2) Generate Theory



5) Analyse Data



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We have now conducted the first three phases of the scientific method

4. Collect data to test theory.So in line with our hypothesis that Hypoxia will decrease VO2max:

We need to measure the variable(s) we have identified:

Independent variable: Hypoxia / Normoxia (environmental chamber) Dependant variable: VO2max (treadmill, direct or method)

The data collection process is often considered the easiest part of the research process – often routine, such as repeated VO2max tests. However.........

Planning the method is one of the most difficult steps of the research process

A good method will help you by:

- Maximising the validity and reliability of the study

- Ensure the data collected is not biased, i.e. is representative of the population

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Good results need Validity and ReliabilityGood methods maximise internal and external validity, and reliability:

Validity: Evidence that a study allows correct inferences about the question it was aimed to answer, or, that a test measures what it set out to measure conceptually.

Internal validity: The extent to which the results of the study can be attributed to the treatments (interventions) used in the study.“Alternative explanations” - subject performed extra training outside of intervention, they took a supplement....hence why experimental control so important control...control...control

External validity: The generalizability of the results of the study.People, places, times, random sample selection, etc. Use control groups and randomisation to augment external validity. Duplicate samples also augment external validity.

Reliability: Whether an instrument can be interpreted consistently across different situations, the results repeated, can include equipment / protocols.Significant results are not “one of events” and are inherently repeatable, e.g. other scientists should be able to perform exactly the same experiment and generate the same results.

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VO2max50 ± 5.0 ml.kg.min-1

Pre VO2max52 ± 3.0 ml.kg.min-1

Post VO2max70 ± 5.0 ml.kg.min-1

10 wks - Live High Train Low

Altitude Training

-3SD -2SD -1SD 50 ml +1SD +2SD +3SD

Freq

uenc

y of

a sc

ore

68%

95%

99%

Population Mean = 50 ± 5.2

-15ml -10ml -5ml 50ml +5ml +10ml +15ml

35ml 40ml 45ml 50ml 55ml 60ml 65ml

Internal Validity

VO2max50 ± 5.0 ml.kg.min-1

Pre VO2max52 ± 3.0 ml.kg.min-1

Post VO2max70 ± 5.0 ml.kg.min-1

10 wks - Live High Train Low

Altitude Training



Post VO2maxPre VO2max

6. Generalisations can only be made about your sample.

5. Descriptive StatisticsCentral Tendency & Dispersion

4.Data collection

5. Inferential statisticsComparison of means, regression and correlation.

6. Generalisations (inference) can be extrapolated from your sample data to the wider population your sample is drawn from.

5. Data tested and analysed

Sampling

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External Validity

Data

Identify Variables

Measure Variables



2) Generate Theory



5) Analyse Data

6) Discuss the meaning and implications of the findings/results


We have now conducted the first four phases of the scientific method28

5. Analysing DataStatistical analysis is performed to aid acceptance or rejection of the null hypothesis.

Two types of statistics are generally employed:

Descriptive statistics: Allow you to describe the basic features, i.e. the central tendency (mean, median & mode) and variability/dispersion (standard deviation & range) of your data. They can be used to consolidate a large amount of data into a simple summary. They do not allow you to make judgements beyond your sample to the population your sample was taken from.

Inferential statistics: With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. Specifically, we use inferential statistics to make judgements of the probability (P value) that an observed difference or relationship within or between groups is a dependable one or one that might have happened by chance. This allows us to draw conclusions that extend beyond the immediate data generated from your specific sample, therefore, allowing inferences to made to population your sample was taken from.

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Data tested and analysed

Sampling

4.Data collection


6. Generalisations can be extrapolated from your sample data to the wider population your sample is drawn from.


Sampling

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Analysis Parametric Non-parametric

Relationship between two variables(continuous data)

Pearson correlation Spearman signed rank test

Relationship between two variables (categorical data)

-------- Chi-squared test for no association

Comparing 2 means(different participants)

Unpaired (independent) t test Mann-Whitney U test

Comparing 2 means(same participants)

Paired (dependent)t test

Wilcoxon signed rank test

Comparing 3 or more means (different participants)

One-Way between-subject ANOVA Kruskal-Wallis test

Predicting a dependent variable from one independent variable

Simple linear regression --------

Predicting a dependent variable from more than one predictor variable

Multiple linear regression --------

Comparing 3 or more means (same participants)

Repeated measures one-way ANOVA Friedman test

Comparing 2 or more means (different participants) but two between-subject variables

Factorial between-subjects ANOVA --------

Comparing 2 or more means but one within-subject variable and one between-subject variable

Mixed model ANOVA --------31




Sampling

4.Data collection




Sampling

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Data

Identify Variables

Measure Variables



2) Generate Theory



5) Analyse Data



We have now conducted the first 5 phases of the scientific method33

6. Discussing the meanings, implications , future directions and real world applications of findings.

Example: Our hypotheses that Hypoxia will decrease VO2max was proved correct:

-To gain an accurate measure of an individuals true VO2max, tests must be conducted at sea level.

- Comparison of VO2max values obtained at altitude (hypoxia) can not be securely made to those obtained at sea level.

- Training intensity is lower at altitude, compared to sea level, and thus altitude training reduces training load – hence why the modern paradigm is “live high train low”.

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Sampling

4.Data collection




Sampling

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Data

Identify Variables

Measure Variables



2) Generate Theory



5) Analyse Data



We have now conducted the all phases on the scientific method36

week 17 the scientific method lecture lm

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