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Chapter 15: Regression
Multiple choice questions
Multiple choice questions
This activity contains 10 questions.
A line of best fit is also known as a:
Difference in means
Discriminant variate
Regression equation
Significance value
The r-square statistic is the:
Proportion of variance accounted for by the independent variables
Square root of the sample size
Standardized beta weight
Statistical significance of the dependent variables, as a set
Standardized beta values:
Cannot take a negative value
Lie between -1 and +1
Range from 0 to 1
Run from -1 to infinity
Multicollinearity means that:
Dependent variables are measured on the wrong scale
Dummy coding should be used for independent variables
Independent variables are too highly correlated
The independent variables account for too much variance in the dependent variable
As a general rule of thumb, the sample size required for testing the overall relationship in multiple regression is:
At least 50 participants and then another 8 per variable
At least 104 participants plus the number of variables
At least 250 participants
Ten participants per variable
As a general rule of thumb, the sample size required for testing the individual pathways in multiple regression is:
At least 50 participants and then another 8 per variable
At least 104 participants plus the number of variables
At least 250 participants
Ten participants per variable
Which one of these types of multiple regression is used to enter variables in a pre-determined order?
Backward
Hierarchical
Simultaneous
Stepwise
Which one of these standardized beta weights is the largest?
-.60
.01
.23
.73
A multiple regression where there is only one independent variable, will produce the same result as a:
ANOVA
Correlation coefficient
p
value
t-test
A multiple regression is used to predict students' exam results from their negative attitudes to statistics (β = -.20), statistical anxiety (β = -.43), cognitive ability (β = .43) and hours spent revising (β = .45). Which is the best predictor of exam results?
Cognitive ability
Hours spent revising
Negative attitudes to statistics
Statistical anxiety
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