Exam 14: Simple Linear Regression

Exhibit 14-4 Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x n = 17 SSR = 225 SSE = 75 S_b1 = 0.2683 -Refer to Exhibit 14-4. The t statistic for testing the significance of the slope is

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Exhibit 14-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 14-5. The coefficient of determination is

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The point estimate of y when x = 10 is

In a regression analysis, the variable that is being predicted

Exhibit 14-7 You are given the following information about y and x. -Refer to Exhibit 14-7. The sample correlation coefficient equals

In a regression analysis, the coefficient of determination is 0.4225. The coefficient of correlation in this situation is

If there is a very strong correlation between two variables then the coefficient of determination must be

If two variables, x and y, have a strong linear relationship, then

Assume you have noted the following prices for books and the number of pages that each book contains. a.Perform an F test and determine if the price and the number of pages of the books are related. Let $\alpha$ = 0.01. b.Perform a t test and determine if the price and the number of pages of the books are related. Let $\alpha$ = 0.01. c.Develop a 90% confidence interval for estimating the average price of books that contain 800 pages. d.Develop a 90% confidence interval to estimate the price of a specific book that has 800 pages.

Exhibit 14-6 For the following data the value of SSE = 0.4130. -Refer to Exhibit 14-6. The total sum of squares (SST) equals

A regression analysis between demand (Y in 1000 units) and price (X in dollars) resulted in the following equation = 9 - 3X The above equation implies that if the price is increased by $1, the demand is expected to

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

Exhibit 14-2 You are given the following information about y and x. -Refer to Exhibit 14-2. The least squares estimate of b₀ (intercept)equals

Exhibit 14-3 You are given the following information about y and x. -Refer to Exhibit 14-3. The least squares estimate of b₁ equals

The interval estimate of an individual value of y for a given value of x is

An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 months was taken. The results of the sample are presented below. The estimated least squares regression equation is = 75.061 - 6.254X a.Obtain a measure of how well the estimated regression line fits the data. b.You want to test to see if there is a significant relationship between the interest rate and monthly sales at the 1% level of significance. State the null and alternative hypotheses. c.At 99% confidence, test the hypotheses. d.Construct a 99% confidence interval for the average monthly sales for all months with a 10% interest rate. e.Construct a 99% confidence interval for the monthly sales of one month with a 10% interest rate.

Exhibit 14-5 The following information regarding a dependent variable (Y) and an independent variable (X) is provided. -Refer to Exhibit 14-5. The MSE is

A least squares regression line

The following data represent the number of flash drives sold per day at a local computer shop and their prices. a.Perform an F test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01. b.Perform a t test and determine if the price and the number of flash drives sold are related. Let $\alpha$ = 0.01.