QMB 3200 Chapter 14 Practice test
Observations with extreme values for the independent variables are called:
high leverage points.
A graph of the standardized residuals plotted against values of the normal scores that helps to determine whether the assumption that the error term has a normal probability distribution appears to be valid is called a:
normal probability plot.
The tests of significance in regression analysis are based on assumptions about the error term ɛ. One such assumption is that the error term follows ɛ a(n) _____ distribution for all values of x.
normal.
The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is called a(n):
residual.
If a residual plot of x versus the residuals, y - ŷ, shows a non-linear pattern, then we should conclude that:
the regression model is not an adequate representation of the relationship between the variables.
The tests of significance in regression analysis are based on assumptions about the error term ɛ . One such assumption is that the variance of ɛ, denoted by 𝝈2, is:
the same for all values of x.
If a significant relationship exists between x and y and the coefficient of determination shows that the fit is good, the estimated regression equation should be useful for:
estimation and prediction.
The following data show the results of an aptitude test and the grade point average of 10 students. The t test for a significant relationship between GPA and Aptitude Test Score is based on a tdistribution with _____ degrees of freedom.
df for T-test do N-2... 10-2 = 8
The model developed from sample data that has the form is known as the:
estimated regression equation.
The tests of significance in regression analysis are based on assumptions about the error term ɛ. One such assumption is that the values of ɛ are:
independent.
When studying the relationship between two quantitative variables, whenever we want to predict an individual value of y for a new observation corresponding to a given value of x, we should use a(n):
prediction interval.
