BUS 222 Exam 1 T/F Questions
An example of a dummy variable is "time to product's first repair" in years.
False
For the hypothesis test, H0: σ1^2 = σ2^2, with n1 = 10 and n2 = 10, the F-test statistic is 2.56. At the 0.02 level of significance, we would reject the null hypothesis.
False
In a multiple regression equation with three independent variables, X1, X2, and X3, the interaction term is expressed as (Y)(X1).
False
In an ANOVA table, k represents the total number of sample observations and n represents the total number of treatments.
False
In multiple regression analysis, a residual is the difference between the value of an independent variable and its corresponding dependent-variable value.
False
In regression analysis, error is defined as.
False
Interaction between two factors occurs when the effect of one factor on the response variable is the same for any value of another factor.
False
Stepwise regression analysis is also called a "backward elimination" method.
False
The alternative hypothesis used in ANOVA is H1: All population means are equal.
False
The coefficient of determination is the square root of the coefficient of correlation.
False
The coefficient of multiple determination, R2, reports the proportion of the variation in Y that is not explained by the variation in the set of independent variables.
False
The null hypothesis to test the slope of a regression equation is H0: α = 0.
False
A correlation matrix can be used to assess multicollinearity between independent variables.
True
An economist is interested in predicting the unemployment rate based on gross domestic product. As the economist is interested in predicting unemployment, the independent variable is gross domestic product.
True
As the coefficient of determination is expressed as a percent, its value is between 0% and 100%.
True
Correlation analysis is a statistical technique used to measure the strength of the relationship between two variables.
True
For a global test of a multiple regression equation, the F-distribution is defined by the regression and residual degrees of freedom.
True
For an ANOVA test, rejecting the null hypothesis does not identify which treatment means differ significantly.
True
If we want to determine which treatment means differ, we compute a confidence interval for the difference between each pair of means.
True
In a multiple regression analysis, if the regression coefficient of a dummy variable is significant and has a sample coefficient value of 100, then the dummy variable's effect on the dependent variable is an increase of 100.
True
In a two-way ANOVA with interaction, there are two factor effects and an interaction effect.
True
In multiple regression analysis, an F-statistic is used to test the global hypothesis, H0: All βi = 0.
True
The coefficient of determination is the proportion of total variation in Y that is explained by X.
True
The least squares technique minimizes the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y.
True
The regression equation is used to estimate a value of the dependent variable Y based on a selected value of the independent variable X.
True
The values of a and b in the regression equation are called the regression coefficients.
True
The variance inflation factor (VIF) is used to select or remove independent variables to reduce the effects of multicollinearity in a multiple regression equation.
True
To employ ANOVA, the populations should have approximately equal standard deviations.
True
When a blocking effect is included in an ANOVA, the analysis is more likely to detect differences in the treatment means.
True
When a blocking effect is included in an ANOVA, the result is a smaller error sum of squares.
True
