Chapter 4 Regression Models

51) A high correlation always implies that one variable is causing a change in the other variable.

52) A dummy variable can be assigned up to three values.

53) The number of dummy variables must equal 1 less than the number of categories of the qualitative variable.

54) Which of the following statements is true regarding a scatter diagram?

A) It provides very little information about the relationship between the regression variables.

B) It is a plot of the independent and dependent variables.

C) It is a line chart of the independent and dependent variables.

D) It has a value between -1 and +1.

E) It gives the percent of variation in the dependent variable that is explained by the independent variable.

55) A reference to the criterion used to select the regression line, to minimize the squared distances between the estimated straight line and the observed values is called

A) Mean square error.

B) Sum of Squares.

C) Maximum likelihood.

D) R-square.

E) Least Squares.

56) The random error in a regression equation

A) is the predicted error.

B) includes both positive and negative terms.

C) will sum to a large positive number.

D) is used to estimate the accuracy of the slope.

E) is maximized in a least squares regression model.

57) Which of the following statements is/are not true about regression models?

A) Estimates of the slope are found from sample data.

B) The regression line minimizes the sum of the squared errors.

C) The error is found by subtracting the actual data value from the predicted data value.

D) The dependent variable is the explanatory variable.

E) The intercept coefficient is not typically interpreted.

58) Which of the following equalities is correct?

A) SST = SSR + SSE

B) SSR = SST + SSE

C) SSE = SSR + SST

D) SST = SSC + SSR

E) SSE = Actual Value - Predicted Value

59) The sum of squared error (SSE) is

A) a measure of the total variation in Y about the mean.

B) a measure of the total variation in X about the mean.

C) a measure in the variation of Y about the regression line.

D) a measure in the variation of X about the regression line.

E) None of the above

60) If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that

A) Y = a + bX is a good forecasting method.

B) Y = a + bX is not a good forecasting method.

C) a multiple linear regression model is a good forecasting method for the data.

D) a multiple linear regression model is not a good forecasting method for the data.

E) None of the above