Research Methods and Statistics Chapter 3, 6, 7, 8 and 10 (Different Research Claims)

Question 1

What are the three types of research claims

Answer 1

1. Frequency claims (proportions of variable of population)
2. Association claim (association between variables)8
3. Causal claim (one variable causes another)

Question 2

What are the 4 big validities

Answer 2

4. External validity (can we generalize the research to other population and operationalizations)
5. Construct validity (does the measure really measure what it is supposed to measure?)
6. Internal validity (what is the causation –> only in experiments)
7. Statistical validity (comparing the values from both conditions)
   Is there an effext?

–>

Question 3

Whats a thematic apperception test

Answer 3

Letting a person write a story about a picture and valuing the emotions

Question 4

What is the most ideal design for frequency claim

Answer 4

Surveys and also observational research

Question 5

What’s the most ideal research design for association claims

Answer 5

Correlational research

Question 6

What are the 6 types of probability sampling

Answer 6

1. Simple random sample (everybody of population has same chance to participate) (very hard but most important)
2. Cluster sample (everybody in a category like schools or organisations)
3. Multistage sampling (sample random subjects of clusters)
4. Stratford random sampling (sample according to percentages like blood types)
5. Oversampling (sampling more of a specific minority)
6. Systematic sampling (every nth person)

–> is a representative sample which can be generalised

Question 7

What are the types of non probability sampling

Answer 7

1. Convenience sampling (accessible samples)
2. Purposive sampling (search for samples with specific requirements)
3. Snowball sampling (ask subjects for other fitting subjects)
4. Quota sampling (set a quota and fulfill them)

–> can not be generalised to population

Question 8

Where is good sampling important

Answer 8

In frequency claims

It is not that important in causal and association claims

Question 9

What are the 3 challenges in observational research

Answer 9

1. Observer effect (observer affects subjects behaviour)
2. Observer bias (your expectations affect your observations)
3. Reactivity (subjects behave differently when they know that they are being observed)

Question 10

What are solutions against observer effect and observer bias

Answer 10

1. Unambiguous codebook
2. Multiple observers
3. Masked design (observers are unaware of studies purpose)

Question 11

What are solutions to reactivity problem

Answer 11

1. Blend in (making yourself less noticable)
2. Wait it out (subjects will get used to presence after some time)
3. Unobstrusive (study evidence for behaviour)

Question 12

What is the challenge in correlational research

Answer 12

Correlation doesn’t say anything HOW the association works

• A causes B
• B causes A
• C causes A and B

Question 13

What are the three criterias for a causal claim

Answer 13

1. Covariance (there is an effect)
2. Temporal precedence (the causal came before the effect)
3. Internal validity (there are no confounds)

Question 14

What is a bivarate correlation

Answer 14

A association that involves exactly 2 variables

Question 15

How do you interrogate statistical validity

Answer 15

1. Effect size: (How big is effect size)
2. Measure statistical significance (is it surely not just by chance?)
3. Measure potential outliers (are there any values affecting the results)
4. Restriction of range (is the range not big enough?)
5. Curvilinear (is the association maybe a curve?)

Question 16

How do you interrogate internal validity?

Answer 16

Did you maybe see the association as a causal effect?

Question 17

How do you interrogate external validity?

Answer 17

Is the sample really representative of the population?

Question 18

Why are surveys sometimes not valid

Answer 18

1. The words in the question may Influence the answers

2. People want to make themselves look good

Question 19

Why are surveys sometimes not valid

Answer 19

1. The words in the question may Influence the answers

2. People want to make themselves look good

Question 20

Whats the difference between observational and experimental research

Answer 20

In observational research you just measure the conditions (IV) nature produced and the variation (DV) from that.
In experimental research you produce the condition (IV) yourself to then see the variation (DV). Only here causal claims are possible.

Question 21

What is generalizability

Answer 21

When a theory is supported by both observational and experimental studies (Replication)

Question 22

What are the pros and cons of experimental and observational research

Answer 22

Experimental can be very hard, unethical and unnatural, but you have control and can achieve causality.
Observational is possible to have confounds and there is no direct causality, but it is easier to do and its more natural

Question 23

What are the four big things that can go wrong in an experimental design and which thread internal validity

Answer 23

1. Design confounds (Your manipulation can cause multiple variations –> confounds)
2. Selection effects (Systematic differences between groups (nonrandom or selection bias))
3. Pseudoreplication (replication is not done right as subjects may come from same enviroment)
4. Order effects (Systematic differences because you measured the conditions always the same –> solution is counterbalancing (mixing up the orders))

Question 24

Explain a between group design

Answer 24

A between group design (indepent) means different participants are used for each group and condition. It is more sure, but there may be selection effects

Question 25

Explain the two designs for between group experiments

Answer 25

1. Post-test design (Assume no difference between groups and measure the difference in the dependent variable AFTERWARDS)
2. Pretest/Posttest design (measure the difference in the dependent variable BEFORE and AFTERWARDS, and then measure the difference in the difference)

Question 26

Explain a within-groups design

Answer 26

A within-groups design has every participants test all the levels of independent variable
The advantage is that you need fewer participants, but there may be order effects and demand characteristics

Question 27

Explain the different within-groups designs

Answer 27

1. Repeated measure design (measure the dependent variable in every participant after each exposure to the independent variable)
2. Concurrent measure design (present both conditions and see which one is preferred (babies prefer warmth over food)