Under what circumstances will residual scores be large? (Points : 1)
Whenever sample sizes are small
When x is a weak predictor of y
When the relationship between x and y is negative
Whenever range is attenuated
Question 2 of 10 The correlation value, which is the equivalent of Pearson Correlation when there are multiple x variables, is _____________. (Points : 1)
Spearman’s rho
the point-biserial correlation
phi coefficient
multiple correlation
Multiple regression refers to ______________. (Points : 1)
a regression solution with multiple values of y
a regression procedure that can be used many times
a regression procedure with multiple criterion variables
a regression procedure with multiple predictor variables
Question 4 of 10 The criterion variable in regression is ____________. (Points : 1)
the variable that indicates the correlation between x and y
the variable used to predict the value of y
the variable for which the value is predicted
the independent variable in regression
The criterion variable in regression is also called the dependent variable. (Points : 1)
True
False
More widely scattered points in the scatterplot indicate ____________. (Points : 1)
more variability in the x variable
more variability in the y variable
normality in both variables
weaker relationships between variables
The least-squares criterion requires which of the following? (Points : 1)
Values with the lowest values make the best predictors
The square of the regression solution is the best predictor
The lowest number of subjects that will provide a prediction is best
The square of error values must have their lowest possible value
The intercept value in a regression solution indicates where the regression line crosses the x axis. (Points : 1)
True
False
The n-1 in the denominator of a correlation formula indicates _________. (Points : 1)
a multiple correlation
a negative correlation
a correlation designed for a group of data of any size
a correlation from sample data
A residual score is ____________. (Points : 1)
the difference between actual y and the predicted value of y
a score not used in a regression solution
the predicted value of y as a result of the regression solution
a score left over after calculating a correlation