Bivariate Correlations
Interrogating Association Claims
Practical Applications and Effect Size
Validity in Research
Moderation in Research
100

What are the two variables in Bivariate Correlations?

Quantitative and Categorical

100

Describe statistical and construct validity. 

Statistical- how well the data supports the conclusions drawn from the study

Construct- how well each variable is measured

100

What context do we call the ‘strength of relationships’?

Effect size 

100

True or false

Researchers should not consider potential third variables that may confound the relationship between the primary variables of interest.

False 

Researchers SHOULD consider potential third variables that may confound the relationship between the primary variables of interest.

100

True or false 

Moderators are variables that affect the time or direction of the relationship between two other variables, indicating that the relationship may vary based on the level of the moderator.

False 

Moderators are variables that affect the STRENGTH or direction of the relationship between two other variables, indicating that the relationship may vary based on the level of the moderator.

200

What is the graphical representation of Bivariate Correlations? What is the correlation coefficient?

Scatterplot (positive, negative, or zero) 

Correlation coefficient = r (strength/direction)

200

What is Internal Validity?

Whether a casual inference can be made from the observed association 
200

What plot do we use when looking at categorical data? What plot do we use when looking at the strength and direction? 

Bar graph

Scatterplot (two continuous variables)

200

Within internal validity is it more or less critical to assess whether a casual relationship can be inferred from the data? 

Less critical 

200

Give an example of a moderator.

Gender, age, cultural background, health status

300

How are quantitative and categorical variables different? 

Quantitative = On a continuum (height, weight)

Categorical = classify participants into distinct categories (gender, race)

300

What is External Validity? 

Considers to whom the results of the study, impacting the applicability of the findings to broader populations
300

True or false: 

Correlational studies cannot support association claims but can establish causation due to the nature of the variable measurement.

False 

Correlational studies can support claims but CANNOT establish causation. 

300

True or false

External validity examines the generalizability of findings to broader populations, emphasizing the importance of sample recruitment methods over sample size.

True 

300

What does a moderator do to the relationship between two variables?

Changes 

400

The design of the study is described as what? 

Correlational

400
What are the two considerations when looking at Construct Validity? 

Operationalization: How were the variables measured? (methods and tools)

Reliability: Questions, consistency (insure measurement accuracy)

400
Which effect size is more likely to be statistically significant? 

Large, medium, small 

Large

400

If a correlational study uses a non-representative sample, the findings may still apply to what?

Different Populations
400

What does a third variable do to the relationship?

Creates a spurious relationship that misrepresents the association between the primary variables 

500

Give the definition of a Bivariate Correlation. 

Bivariate correlations describe the relationship between two measured variables. THINK TWO TWO TWO!!!!

500

Which validity is crucial to the strength of a relationship? 

Statistical validity

500

_____ of studies is crucial for estimating population associations and confirming the reliability of findings. 

Replication

500

True or false

Moderator variables can influence external validity, affecting how findings apply to different contexts or groups.

True

500

What two things are crucial when it comes to distinguishing moderators and third variables? 

Accurate interpretation of research findings and identifying potential confounding factors