BUS 300 Topic 5, Exam 3

B0

Constant, y-intercept

Y

Dependent Variable/Outcome

Residual

Difference between actual Y and predicted Y

U

Error Term

X

Independent/Explanatory Variable

B1

Slope

Regression Equation

Y=B0 + B1(X) + U

In a regression analysis, the regression equation is given by y=12-6x. If SSE=510 and SST=1000, then the correlation coefficient is a - -0.7 b - 0.7 c - 0.49 d - -0.49

a - -0.7

In regression analysis, which of the following is NOT a required assumption about the error team? a - The expected value of the error term is one. b - The variance of the error term is the same for all values of X. c - The values of the error term are independent. d - The error term is normally distributed.

a - The expected value of the error term is one.

A regression analysis between sales Y (in $1000) and price X (in dollars) resulted in the following equation Y = 60 - 8X The above equation implies that an a. increase of $1 in price is associated with a decrease of $8 in sales b. increase of $8 in price is associated with an decrease of $52,000 in sales c. increase of $1 in price is associated with a decrease of $52 in sales d. increase of $1 in price is associated with a decrease of $8000 in sales

a. increase of $1 in price is associated with a decrease of $8 in sales

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is a. 0.4000 b. 0.0256 c. 4 d. 2.56

b. 0.0256

A regression model involved 5 independent variables and 136 observations. The p value of t for testing the significance of each of the independent variable's coefficients will have. a - 121 degrees of freedom b - 135 degrees of freedom c - 130 degrees of freedom d - 4 degrees of freedom

c - 130 degrees of freedom

If the R2 is a positive value, then the correlation coefficient a - Must also be positive b - Must be 0 c - Can be either negative or positive d - Must be larger than 1

c - Can be either negative or positive

In a regression model, the values of the error term, are assumed to be a - zero b - dependent on each other c - independent of each other d - always negative

c - independent of each other

In a regression analysis the standard error is derterminded to be 4. In this situations the MSE is a - 2 b - 6 c - Depends on the sample size d - Depends on the degrees of freedom

d - Depends on the degrees of freedom

A regression analysis between sales (Y in $1000) and advertising (X in dollar) resulted in the following equation Y=30,000+4x The above equation implies that an a - Increase of $4 in advertising is associated with an increase of $4,000 in sales b - Increase of $1 in advertising is associated with an increase of $4 in sales c - Increase of $1 in advertising is associated with an increase of $34,000 in sales d - Increase of $1 in advertising is associated with an increase of $4,000 in sales

d - Increase of $1 in advertising is associated with an increase of $4,000 in sales

In a multiple regression model, the error term is assumed to a. have a mean of 1 b. have a variance of zero c. have a standard deviation of 1 d. be normally distributed

d. be normally distributed