Correlations and Regressions 8.1

Question 1

Habituation paradigm

Answer 1

Common method used to test the
mental categories of nonverbal
infants and nonhuman animals

Question 2

Habituation paradigm method

Answer 2

• Habituate an organism to a
stimulus.

• Present a new stimulus.
(If they remain habituated, it means they treat it as the same category. If they don’t then they recognize it as categorically different)

• DV: difference score

• Can be used experimentally (with control)
or quasi-experimentally (shown here)

Question 3

Correlation Research Types

Answer 3

• Causality
• Correlation (describe relationships) and Regression (predictions)
• Spurious correlations
• Regressions

Question 4

Correlations

Answer 4

• tell you the relationship between two 
(bivariate) or more (multivariate) 
variables
• Which variable is X, and which is Y 
does not matter
• The correlation coefficient for linear 
relationships (r) ranges from -1 to +1
• Correlations can be positive or negative, 
and differ in strength

Question 5

Correlation does not imply causation!

Answer 5

Spurious correlations – relationships that are correlated but not causally
related

Question 6

Third variable

Answer 6

Third variable – a variable that causes changes in other variables and thus explains the
correlation

Question 7

Regressions

Answer 7

Statistical models that allow you to predict the outcome of one variable based on
the values of another variable
• The regression line is the best-fit line (it minimizes error)

Question 8

Simple linear regression

Answer 8

• 2 continuous variables
• y = a + bx
• y = response variable (DV)
• x = predictor variable (IV)
• b = regression coefficient (+/-)

Question 9

Multiple linear regression

Answer 9

• y = a + b1x1 + b2x2 + … + bixi
• Complex relationships
• Controlling for other factors

Question 10

Logistic regression

Answer 10

• Use a continuous variable to predict a binary categorical variable
• Reminder: causal relationships are warranted based on data collection methods, not models
or the names of the variables

Question 11

Interpolation vs extrapolation

Answer 11

Extrapolation: prediction that go beyond the data