Exam 13: Multiple Regression

Using a sample of 63 observations,a dependent variable Y is regressed against two variables X1 and X2 to obtain the fitted regression equation Y = 76.40 − 6.388X1 + 0.870X2.The standard error of b1 is 3.453 and the standard error of b2 is 0.611.At α = .05,we could

A squared predictor is used to test for nonlinearity in the predictor's relationship to Y.

The t test shows the ratio of an estimated coefficient to its standard error.

Confidence intervals for Y may be unreliable when the residuals are not normally distributed.

The first differences transformation might be tried if autocorrelation is found in a time-series data set.

In the following regression (n = 91),which coefficients differ from zero in a two-tailed test at α = .05?

In the following regression,which are the three best predictors?

Given that the fitted regression is Y = 76.40 − 6.388X1 + 0.870X2,the standard error of b1 is 1.453,and n = 63,at α = .05,we can conclude that X1 is a significant predictor of Y.

The effect of a binary predictor is to shift the regression intercept.

The residual plot below suggests which violation(s)of regression assumptions?

A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars)as a function of Size (measured in thousands of square feet)and whether or not there is a fireplace (FP is 0 if there is no fireplace,1 if there is a fireplace).The regression output is provided below.Some of the information has been omitted. Which of the following conclusions can be made based on the F-test?

For a certain firm,the regression equation Bonus = 2,000 + 257 Experience + 0.046 Salary describes employee bonuses with a standard error of 125.John has 10 years' experience,earns $50,000,and earned a bonus of $7,000.John is an outlier.

In a multiple regression with k independent variables,the standard error is

Refer to the following correlation matrix that was part of a regression analysis.The dependent variable was Abort (the number of abortions per 1000 women of childbearing age).The regression was estimated using data for the 50 U.S.states with these predictors: EdSpend = public K−12 school expenditure per capita,Age = median age of population,Unmar = percent of total births by unmarried women,Infmor = infant mortality rate in deaths per 1000 live births. Correlation Matrix Using a two-tailed correlation test,which statement is not accurate?

Refer to the following regression results.The dependent variable is Abort (the number of abortions per 1000 women of childbearing age).The regression was estimated using data for the 50 U.S.states with these predictors: EdSpend = public K − 12 school expenditure per capita,Age = median age of population,Unmar = percent of total births by unmarried women,Infmor = infant mortality rate in deaths per 1000 live births. Which statement is not supported by a two-tailed test?

Which statement is incorrect?

A fitted multiple regression equation is Y = 12 + 3X1 - 5X2 + 7X3 + 2X4.When X1 increases 2 units and X2 increases 2 units as well,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

In a regression with 7 predictors and 62 observations,degrees of freedom for a t test for each coefficient would use how many degrees of freedom?

Part of a regression output is provided below.Some of the information has been omitted. The SS (residual)is

If R2 and R2adj differ greatly,we should probably add a few predictors to improve the fit.