The manager of a chain of furniture stores believes that experience is the most important factor in determining the level of success of a salesperson. To examine this belief he records last month's sales and the years of experience for 30 randomly selected salespeople. The linear regression output to predict Monthly Sales (in $1,000's) based on Years of Experience is: please refer to the photo at the bottom

Question 1:

Construct a 90% confidence interval for the population slope.

Round values to the dollar (whole number)

One can be 90% confident the population slope is between $ ? (lower value) and $ ? (upper value)

Question 2:

One of your salespeople has12 years of experience. Use the results from the regression to predict their monthly sales.(Round to the nearest dollar, as applicable)

Predicted Monthly Sales =?

Question 3:

A salesperson with 12 years of experience had $25,000 in sales last month. Is this low for a salesperson with 12 years experience? Explain.(Select ALL that apply)

a) Yes. $25,000 in sales is LOW

b) No. $25,000 in sales is NOT low for 12 years experience.

c) Because it is NOT THE SAME as the sales amount predicted

d) Because it is CLOSE to the sales amount predicted

e) Because it is A LOT MORE than the sales amount predicted

f) Because it is A LOT LESS than the sales amount predicted

Question 4:

Interpret the coefficient of determination, r², using the words of the problem.

a) 47.9% of the variation (how it increases and decreases) in monthly sales can be explained by the years of experience of an employee

b) 47.9% of the variation (how it increases and decreases) in the years of experience of an employee can be explained by monthly sales

c) 47.9% of the values are in a linear pattern

d) 69.21% of the values are in a linear pattern

e) 69.21% of the variation (how it increases and decreases) in monthly sales can be explained by the years of experience of an employee

f) 69.21% of the variation (how it increases and decreases) in the years of experience of an employee can be explained by monthly sales

Question 5:

What is the value that should be used for the null hypothesis?

H₀:?₁? _____________

Question 6:

What is the alternate hypothesis?

a) H_A:?₁

b) H_A:?₁

c) H_A:?₁> 1.82

d) H_A:?₁? 0

e) H_A:?₁> 0

f) H_A:?₁? 1.82

Question 7:

What is the p-value for this hypothesis test? (Answer as PERCENTAGE, to 4 decimal places)

Question 8:

At the 5% significance level, should you reject the null hypothesis? Is there enough evidence to conclude there is a linear relationship between monthly sales and years of experience?

(Select ALL answers that apply)

a) REJECT the null hypothesis

b) Do NOT reject the null hypothesis

c) Yes, there is ENOUGH evidence to conclude there is a LINEAR relationship

d) No, there is NOT enough evidence to conclude there is a LINEAR relationship

SUMMARY OUTPUT Regression Statistics Multiple R 0.6921 R Square 0.479 Observations 30 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 18.5 4.608 4.017 0.000401 9.1 27.9 Years of Experience 1.82 0.3587 5.074 0.000023 1.09 2.55