QMB 3200 A ANSWERS AND QUESTIONS SET A+
✔✔In a multiple regression model, the values of the error term, ε, are assumed to be -
✔✔Normally distributed
✔✔In multiple regression analysis - ✔✔there can be several independent variables, but
only one dependent variable.
✔✔The study of how a dependent variable y is related to two or more independent
variables is called - ✔✔multiple regression analysis.
✔✔The mathematical equation relating the expected value of the dependent variable to
the value of the independent variables, which has the form of
E(y)=B0+b1x1+b2x2+...+Bpxp, is called - ✔✔A multiple regression equation.
✔✔Dummy variables must always have - ✔✔Values of either 0 or 1
✔✔The term in the multiple regression model that accounts for the variability in y that
cannot be explained by the linear effect of the p independent variables is the - ✔✔error
term
✔✔When we use the estimated regression equation to develop an interval that can be
used to predict the mean for a specific unit that meets a particular set of given criteria,
that interval is called a(n) - ✔✔Prediction
✔✔The proportion of the variability in the dependent variable that can be explained by
the estimated multiple regression equation is called the - ✔✔Multiple coefficient of
determination
✔✔If a categorical variable has k levels, then - ✔✔K-1 dummy variables are needed.
✔✔In a multiple regression model, the values of the error term, ε, are assumed to be -
✔✔Independent of each other
, ✔✔The method used to develop the estimated regression equation that minimizes the
sum of squared residuals is called the - ✔✔least squares method.
✔✔The mathematical equation that explains how the dependent variable y is related to
several independent variables and has the form y=B0+b1x1+b2x2+....Bpxp+e is called -
✔✔A multiple regression model.
✔✔When we conduct significance tests for a multiple regression relationship, the t test
can be conducted for each of the independent variables in the model. Each of those
tests are called tests for - ✔✔Individual significance.
✔✔In a multiple regression model, the error term ε is assumed to have a mean of - ✔✔0
✔✔In general, R2 always _____ as independent variables are added to the regression
model. - ✔✔Increases.
✔✔The multiple regression equation based on the sample data, which has the form of
y^ hat= b0+b1x1+b2x2+....+bpxp, is called - ✔✔An estimated multiple regression
equation.
✔✔Looking at the sample correlation coefficients between the response variable and
each of the independent variables can give us a quick indication of which independent
variables are, by themselves, - ✔✔Good predictors.
✔✔When carrying out an F test to determine if the addition of extra predictor variables
results in a significant reduction in the error sum of squares, what are the degrees of
freedom of the numerator and denominator of the F statistic? - ✔✔The numerator
degrees of freedom equals the number of predictors added to the model. The
denominator degrees of freedom is n—p—1.
✔✔The regression model y=B0+B1x1+B2x2+B3x2^2+B4x2^2+B5x1x2+e is a -
✔✔second-order model with two predictor variables.
✔✔What test can be used to determine whether first-order autocorrelation is present? -
✔✔Durbin-Watson test
✔✔With negative autocorrelation, we expect a positive residual in one period to be
followed by - ✔✔a negative residual in the next period, then a positive residual, and so
on.
✔✔When autocorrelation is present, which of the following assumptions is violated? -
✔✔The error terms are independent.
✔✔In a multiple regression model, the values of the error term, ε, are assumed to be -
✔✔Normally distributed
✔✔In multiple regression analysis - ✔✔there can be several independent variables, but
only one dependent variable.
✔✔The study of how a dependent variable y is related to two or more independent
variables is called - ✔✔multiple regression analysis.
✔✔The mathematical equation relating the expected value of the dependent variable to
the value of the independent variables, which has the form of
E(y)=B0+b1x1+b2x2+...+Bpxp, is called - ✔✔A multiple regression equation.
✔✔Dummy variables must always have - ✔✔Values of either 0 or 1
✔✔The term in the multiple regression model that accounts for the variability in y that
cannot be explained by the linear effect of the p independent variables is the - ✔✔error
term
✔✔When we use the estimated regression equation to develop an interval that can be
used to predict the mean for a specific unit that meets a particular set of given criteria,
that interval is called a(n) - ✔✔Prediction
✔✔The proportion of the variability in the dependent variable that can be explained by
the estimated multiple regression equation is called the - ✔✔Multiple coefficient of
determination
✔✔If a categorical variable has k levels, then - ✔✔K-1 dummy variables are needed.
✔✔In a multiple regression model, the values of the error term, ε, are assumed to be -
✔✔Independent of each other
, ✔✔The method used to develop the estimated regression equation that minimizes the
sum of squared residuals is called the - ✔✔least squares method.
✔✔The mathematical equation that explains how the dependent variable y is related to
several independent variables and has the form y=B0+b1x1+b2x2+....Bpxp+e is called -
✔✔A multiple regression model.
✔✔When we conduct significance tests for a multiple regression relationship, the t test
can be conducted for each of the independent variables in the model. Each of those
tests are called tests for - ✔✔Individual significance.
✔✔In a multiple regression model, the error term ε is assumed to have a mean of - ✔✔0
✔✔In general, R2 always _____ as independent variables are added to the regression
model. - ✔✔Increases.
✔✔The multiple regression equation based on the sample data, which has the form of
y^ hat= b0+b1x1+b2x2+....+bpxp, is called - ✔✔An estimated multiple regression
equation.
✔✔Looking at the sample correlation coefficients between the response variable and
each of the independent variables can give us a quick indication of which independent
variables are, by themselves, - ✔✔Good predictors.
✔✔When carrying out an F test to determine if the addition of extra predictor variables
results in a significant reduction in the error sum of squares, what are the degrees of
freedom of the numerator and denominator of the F statistic? - ✔✔The numerator
degrees of freedom equals the number of predictors added to the model. The
denominator degrees of freedom is n—p—1.
✔✔The regression model y=B0+B1x1+B2x2+B3x2^2+B4x2^2+B5x1x2+e is a -
✔✔second-order model with two predictor variables.
✔✔What test can be used to determine whether first-order autocorrelation is present? -
✔✔Durbin-Watson test
✔✔With negative autocorrelation, we expect a positive residual in one period to be
followed by - ✔✔a negative residual in the next period, then a positive residual, and so
on.
✔✔When autocorrelation is present, which of the following assumptions is violated? -
✔✔The error terms are independent.
