Question 1

Which of the following is a reason why multiple regression designs are inferior to experimental designs?

Accepted Answer

A) They can only control for third variables that are measured. 
B) They cannot establish covariance. 
C) They take longer to conduct. 
D) They are more expensive to conduct. 
A) They can only control for third variables that are measured. 
B) They cannot establish covariance. 
C) They take longer to conduct. 
D) They are more expensive to conduct.

Question 2

Which of the following is a necessary component of a longitudinal design?

Accepted Answer

A) Measuring the same variables at two points in time 
B) Measuring at least four variables at one time 
C) Measuring different age groups at two different times 
D) Manipulating a variable at two points in time 
A) Measuring the same variables at two points in time 
B) Measuring at least four variables at one time 
C) Measuring different age groups at two different times 
D) Manipulating a variable at two points in time

Question 3

In understanding "controlling for" a third variable, which of the following is a similar concept?

Accepted Answer

A) Creating a longitudinal study 
B) Identifying subgroups 
C) Creating an operational definition 
D) Conducting a replication 
A) Creating a longitudinal study 
B) Identifying subgroups 
C) Creating an operational definition 
D) Conducting a replication

Question 4

How do multiple regression designs help rule out third variables?

Accepted Answer

Multiple regression designs help rule ou

Question 5

Why is it problematic when journalists only report on a single study?

Accepted Answer

A) It can make journalists look bad. 
B) It can lead people to think journalists are scientists. 
C) It can lead people to value one study over decades of previous research. 
D) It can cause people to interrogate a study's validities. 
A) It can make journalists look bad. 
B) It can lead people to think journalists are scientists. 
C) It can lead people to value one study over decades of previous research. 
D) It can cause people to interrogate a study's validities.

Which of the following is a reason why multiple regression designs are inferior to experimental designs?

Which of the following is a necessary component of a longitudinal design?

In understanding "controlling for" a third variable, which of the following is a similar concept?

How do multiple regression designs help rule out third variables?

Why is it problematic when journalists only report on a single study?

Psychology Is a Way of Thinking

Sources of Information: Why Research Is Best and How to Find It

Three Claims, Four Validities: Interrogation Tools for Consumers of Research

Ethical Guidelines for Psychology Research

Identifying Good Measurement

Surveys and Observations: Describing What People Do

Sampling: Estimating the Frequency of Behaviors and Beliefs

Bivariate Correlational Research

Introduction to Simple Experiments

More on Experiments: Confounding and Obscuring Variables

Experiments With More Than One Independent Variable

Quasi-Experiments and Small-N Designs

Replication, Generalization, and the Real World

Filters

Exam 9: Multivariate Correlational Research

Which of the following is a reason why multiple regression designs are inferior to experimental designs?

Which of the following is a necessary component of a longitudinal design?

In understanding "controlling for" a third variable, which of the following is a similar concept?

How do multiple regression designs help rule out third variables?

Why is it problematic when journalists only report on a single study?

Psychology Is a Way of Thinking

Sources of Information: Why Research Is Best and How to Find It

Three Claims, Four Validities: Interrogation Tools for Consumers of Research

Ethical Guidelines for Psychology Research

Identifying Good Measurement

Surveys and Observations: Describing What People Do

Sampling: Estimating the Frequency of Behaviors and Beliefs

Bivariate Correlational Research

Introduction to Simple Experiments

More on Experiments: Confounding and Obscuring Variables

Experiments With More Than One Independent Variable

Quasi-Experiments and Small-N Designs

Replication, Generalization, and the Real World

Filters