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### Exam 1 Review

Important topics and some review questions

Models

- Why do we use models?
- What do we look for in a model?

Sample Question

Models must be testable

They don’t have to be perfect

Which of the following models would be most useful to a psychologist who is studying depression?

(a) A model that can explain any results the psychologist might find

(b) A model that makes precise predictions that turn out to be wrong occasionally

Scales of Measurement

- What properties of the number system are relevant to measurement?
- What can we do with interval scales that we can’t do with ordinal scales?

Sample Question

Ordinal scales give information about order

Calculating averages requires an interval scale

I’m fixing dinner for Albert and Brenda. Albert rank orders his preferences: Steak, Fish, Pizza, Chicken. Brenda rank orders them Pizza, Fish, Steak, Chicken. What can I conclude?

(a) Steak and Fish are equivalent

(b) I’d better not fix chicken

Operational Definitions

- Why are operational definitions important?
- What makes a definition operational?

Sample Question

Operational definitions

should tell you what to do

Charlie is studying social adjustment in young children. Which is the least like an operation definition of social adjustment?

(a) A child’s understanding of other children’s feelings

(b) Teachers’ ratings of a child’s social adjustment

(c) A child’s score on a test of social adjustment

Low Constraint Research

- When is it appropriate?
- What are its limitations?

Sample Question

For which of the following topics would low constraint research be most suitable?

(a) Compare two methods for teaching statistics

(b) Find out if training in conflict resolution reduces aggression in teenagers

(c) Find variables related to dating behavior that might be worth studying further

Use low constraint research

for exploration

Sampling Issues

- Why is sampling a concern in research?
- What are the major sampling issues in low constraint research?

Sample Question

Desdemona is interested in the dynamics of family interactions. She spends hours watching all the families that eat at a popular restaurant. Which sampling issue is probably of least concern here?

(a) Participants

(b) Situations

(c) Behaviors

Plenty of participants in this case,

but sample all three of these

Confounding

- Why is confounding a major concern in low constraint research?
- How can one reduce the problems of confounding in low constraint research?

Sample Question

Desdemona observed that expressions of anger by parents are more common in larger families. Which of the following conclusions is appropriate?

If you are the parent of a large family who takes your kids to a restaurant, …

(a) it’s better to take them a few at a time

(b) you can expect to get angry more often than parents of small families

Prediction is OK

Causal inference is not

Differential Research

- What is the purpose of differential research?
- What kind of conclusions can one draw from differential research?

Sample Question

Eric counted children’s use of pronouns in a classroom. He found that tenth graders use the word “We” a lot, fifth graders use it rarely. He concluded that between fifth and tenth grade children acquire an understanding of social groups. What is not a problem with his conclusion?

(a) He may be over-generalizing his results

(b) Cohort effects may influence the results

(c) He has no operational definition for “pronoun”

(d) There may be several confounding variables

Look for other explanations

Correlations

What kind of conclusions can one draw from correlational research ?

How should one interpret the numerical value of a correlation?

Sample Question

Fiona studied recreational runners, and found a correlation of 0.5 between number of injuries and time spent stretching. Which of the following conclusions is appropriate?

(a) Stretching prevents injuries

(b) Stretching makes injuries worse

(c) Having an injury makes people want to stretch more

(d) Stretching explains one quarter of the variance in running injuries

Prediction is assessed by r2

Causal inference is out

Look for other explanations!

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