A life insurance company wishes to examine the relationship between the amount of life insurance held by a family and family income.From a random sample of 18 households, the company collected the data shown below.The data are in units of thousands of dollars.

Let y = INSUR x = INCOME INSUR INCOME

X Y

78 23

132 32

166 33

123 32

162 41

130 34

204 49

346 86

358 85

171 42

308 87

596 142

97 25

204 58

225 55

384 99

246 63

167 37

1 The numerator of the slope coefficient formula for the estimated regression equation is: a 72,973.79 b 71,542.93 c 70,140.13 d 68,764.83

2 The denominator of the slope coefficient formula for the estimated regression equation is: a 17,034.50 b 16,458.45 c 15,901.88 d 15,364.14

3 The vertical intercept of the estimated regression equation is

a -2.398 b -2.086 c -1.814 d -1.577

4 The estimated regression equation predicts that for each additional $1,000 income life insurance policy will rise by _______ ($1,000)

a 6.976 b 5.813 c 4.844 d 4.037

5 The income of one policy holder is 63 ($1000).The predicted life insurance policy is _______ ($1,000)

a 267.655 b 252.505 c 238.212 d 224.728

6 The observed policy amount for the policy holder in previous question is 246 ($1,000) The prediction error is _______.

a -6.505 b -5.995 c -5.525 d -5.093

7 The sum of squared errors (SSE) is,

a 5885.7 b 5552.5 c 5238.2 d 4941.7

8 The sum of squared total (SST) is,

a 306246.7 b 294468.0 c 283142.3 d 272252.2

9 The sum of squared explained deviations (SSR) is,

a 288693.3 b 277589.7 c 266913.2 d 256647.3

10 The observed insurance policy deviates from the predicted policy, on average, by _______ ($1,000) a 18.629 b 17.658 c 16.737 d 15.865

11 The sample data provides that ______ fraction of variations in the life insurance policy is explained by income.

a 0.8674 b 0.9035 c 0.9412 d 0.9804

12 For the purpose of statistical inference for the slope parameter, the standard error of the slope coefficient, se(b), is

a 0.1727 b 0.1570 c 0.1427 d 0.1298

13 The t-score to find the margin of error for a 95% interval estimate of the population slope parameter is,

a 2.226 b 2.120 c 2.019 d 1.923

14 The margin of error for a 95% confidence interval for the population slope parameter is _______ ($1,000),

a 0.303 b 0.288 c 0.274 d 0.261

15 To perform a test of hypothesis that the population slope parameter is zero, the test statistic t is ______.

a 30.005 b 29.131 c 28.282 d 27.459

DEPENDENT VARIABLE = WAGE

Regression Statistics

Multiple R 0.3859

R Square

Adjusted R Square 0.131

Standard Error

Observations 50

DF

Regression: 1

Error:

Total: 49

SS:

Regression:

Error: 6416.6541

Total: 7539.1773

MS:

Regression: 1122.5231

Error:

Fstat:

Regression: 8.3970726

Pvalue:

Regression: 0.00565

b_j se(b_j) t Stat P-value Lower 95% Upper 95%

Intercept: 1.7528 6.4752 0.2707 0.7878 -11.2666 14.7721

EDUC 1.3429 2.89777

16 The predicted WAGE when EDUC = 16 is, a $26.14 b $25.14 c $24.17 d $23.24

17 The fraction of the variations in WAGE explained by EDUC is ________.

a 0.2918 b 0.2084 c 0.1489 d 0.1064

18 Given that the sum of the squared deviations of EDUC is 622.48 The standard error of the slope coefficient is ________.

a 0.4634 b 0.3862 c 0.3218 d 0.2682

19 We are 95% confident that the population slope parameter is between,

a 0.49 2.36 b 0.41 2.27 c 0.34 2.21 d 0.29 2.15

20 The value of the test statistic for H: = 0 is,

a 4.761 b 4.035 c 3.419 d 2.898