Question 7

An insurance company is interested in determining whether there was a relationship between Y = amount insured (in thousands of dollars) and three variables that they believe influenced the amount of insurance that the individual purchased.

These variables are:

X₁ = age of the person who is being insured.

X₂ = The income of the person who is being insured

X₃ = 1 if the person was healthy in terms of build and blood pressure

= 0 otherwise.

To study this further, they took a sample of 64 policies and obtained the following results:

SSR = 200,000

SST = 800,000

Compute the F value for testing: H₀: ₁ = ₂ =₃ =0 against

H₁: at least one of the _i 0

and state whether the results are statistically significant or not.

Question 7 options:

	F = 6.67; Statistically Significant
	F = 30.00; Statistically Significant
	F = 2.44; Not Statistically Significant
	F = 30.00; Not Statistically Significant
	F = 6.67; Not Statistically Significant

Question 8

A regression analysis involving 5 independent variables is carried out, using a total of 25 data points. The following information was obtained:

1. The F test was statistically significant
2. The t-values from the regression coefficient table were respectively: 0.65, -2.91, 3.20, 3.05, and -1.53 for variables 1, 2, 3, 4, and 5.
3. The value of R-squared for the 5 variable model is 0.60.

The variables that should be included in the regression equation are:

Question 8 options:

	Variables 1 and 5.
	Variables 2,3, and 4.
	Variables 1,2, and 5.
	Variables 1,2,4, and 5.
	Variables 3 and 4.

Question 9

A multiple linear regression analysis was carried out using the following data for 48 months of sales of ski equipment for a US company.

Y = Sales (in millions of dollars).

X₁ = Advertising expenditure (in millions of dollars )

X₂ = 1 if the month is in the high season

= 0 if the month is not in the high season

X₃ = X₁ X₂

The results of a regression analysis used to predict sales are as follows:

1. Prediction equation: Y = 50 + 1.20 X₁ + 20X₂ + 0.62X₃

2. The F test is statistically significant.

3. The three T tests are statistically significant.

4. The value of SSR = 16,016.

5. The value of SST = 17,600.

6. The residual plots exhibited a random pattern with no outliers present.

Find a 95% prediction interval for the Sales (in millions of dollars) in a high season month where the advertising expenditure is $11 million.

Question 9 options:

	(47 , 119)
	(54 , 126)
	(71 , 95)
	(78 , 102)
	(84 , 96)