Exam 23: Bivariate Statistical Analysis: Measures of Association

The statistical significance of a regression model is determined using which test?

A correlation matrix is the standard form for reporting observed correlations between two variables.

If the correlation between two variables is -.55, the coefficient of determination is approximately ______.

The statistical significance of a regression model is determined by a F-test.

The correlation coefficient, r, indicates the magnitude of the linear relationships but not the direction of that relationship.

The Pearson product-moment correlation coefficient ranges between _____.

When the on-time performance of airlines is used to predict the number of customer complaints in a regression equation, on-time performance is the ______ variable and the number of customer complaints is the ______ variable.

In a correlation matrix, the values in the main diagonal equal ______.

A(n) _____ is a statistical measure of the covariation, or association, between two at-least interval variables.

The statistical significance of a correlation can be tested using the t-test.

Which of the following is most appropriate if the purpose of the regression analysis is forecasting?

If the correlation between X and Y is -0.72, approximately what percentage of the variance in Y can be explained by X?

Measure of association is a general term that refers to causality.

In simple regression, standardized parameter estimates reflect the measurement scale range.

A correlation coefficient is a measure of the covariance, or association, between two at-least interval variables.

Which regression estimation technique is based on the logic of how much better a regression line can predict values of Y compared to simply using the mean as a prediction for all observations no matter what the value of X may be?

The technique use in regression analysis that guarantees that the resulting straight line will produce the least possible total error in using X to predict Y is called the _____ method.

A rule of thumb for R² is that it must be greater than 0.80 for a regression model to be significant.

In testing for the significance of a correlation, it is hypothesized that the correlation is equal to ______.

The least-squares regression line minimizes the sum of the squared deviations of the actual values from the predicted values in the regression line.