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PSYC 012 CHAPTER 9 INQUIZITIVE EXAM WITH CORRECT ACTUAL QUESTIONS AND CORRECTLY WELL DEFINED ANSWERS LATEST 2024 – 2025 ALREADY GRADED A+ $14.99
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PSYC 012 CHAPTER 9 INQUIZITIVE EXAM
WITH CORRECT ACTUAL QUESTIONS AND
CORRECTLY WELL DEFINED ANSWERS
LATEST 2024 – 2025 ALREADY GRADED A+
Label each scatterplot with the correct description of its results. - ANSWERS-
Numbers spread out = There is an association between exposure to sexual TV
content and pregnancy risk even after the study controls for age.
Numbers not spread out: Age is a third variable that explains the association
between exposure to sexual TV content and pregnancy risk.
Match each validity to the appropriate validity question related to a study on
binge-watching TV and irritability. - ANSWERS-internal validity: Are there any
other variables that explain the association between binge-watching TV and
irritability?
external validity: How was the sample obtained for this longitudinal study?
construct validity:
Was irritability measured in a reliable and valid way?
statistical validity: Is there a curvilinear association between binge-watching TV
and irritability?
,Sammy is interested in studying behavior problems. Identify the multivariate
technique that Sammy should use to investigate each of her research goals.
Labels can be used more than once. - ANSWERS-multiple regression:
Sammy wants to find out whether parenting style explains the association
between self-esteem and behavior problems.
Sammy wants to find out whether self-esteem and behavior problems have a
mutually reinforcing relationship
longitudinal study:
Sammy wants to find out whether self-esteem in elementary school predicts
behavior problems in middle school.
Sammy wants to find out whether self-esteem and behavior problems have a
mutually reinforcing relationship.
Fill in the blanks to complete the passage about variables that influence
associations. - ANSWERS-Additional variables may often add nuance or an
alternative explanation for a relationship. A [ moderator ] is a variable that
explains how the two main variables are related in different ways depending on
the situation. A [ mediator ] explains why two variables may be related based on
an internal factor that connects them.
Fill in the blanks to complete the passage about multiple regression. - ANSWERS-
Multiple regression can help eliminate problems with [ internal validity ] by
controlling for potential third variables. It sets [ predictor ] variable(s) that
influence the [ criterion ] variable, which is the outcome of interest. Effect sizes in
multiple-regression analyses can be represented by both [ beta ], which is a
standardized effect size, and [ b ], which is an unstandardized effect size.
, Identify the true and false statements about pattern and parsimony. - ANSWERS-
True Statement(s):
The pattern and parsimony technique relies on the weight of the evidence from
multiple studies.
The pattern and parsimony technique exemplifies the theory-data cycle.
False Statement(s):
The pattern and parsimony technique works best when all of the studies
surrounding a theory use the same methodology.
The pattern and parsimony technique can be considered only with experiments.
What type of approach do researchers use when they investigate causality with a
variety of correlational studies that all point in a single, causal direction? -
ANSWERS-pattern and parsimony
Fill in the blanks to complete the passage about the types of multivariate
correlational studies. - ANSWERS-A(n) [ longitudinal study ] is conducted over a
longer period of time than a typical correlational study to help establish [
temporal precedence ]. A(n) [ multiple-regression ] analysis considers more than
two variables in the same analysis and can help improve [ internal validity ].
Fill in the blanks to complete the passage about three types of correlations. -
ANSWERS-In a(n) [ cross-sectional correlation ], two variables measured at the
same time are associated. If an earlier measure of a variable is associated with a
later measure of the same variable, a(n) [ autocorrelation ] occurs. In a(n) [ cross-
lag correlation ], an earlier measure of one variable is associated with a later
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