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PLEASE SHOW EXPLAINATION FOR ANSWERS. This assignment extends the analysis of house prices in Springfield (data in House Prices.xlsx ) that was conducted in earlier

PLEASE SHOW EXPLAINATION FOR ANSWERS.

This assignment extends the analysis of house prices in Springfield (data in House Prices.xlsx) that was conducted in earlier assignments.

(a) Consider Model 1 from Individual Assignment 2.Use this regression model to test (at the 5% level of significance) if the average price of a house in the East neighborhood is less than the average pric e of a similar house in the North neighborhood.

Model 1 Output

State the null and alternative hypotheses.

State the p-value for this test.

State the statistical conclusion.

Communicate the results of the test in "plain English" within the context of the problem.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.930384625

R Square

0.86561555

Adjusted R Square

0.857776457

Standard Error

50660.95358

Observations

128

ANOVA

df

SS

MS

F

Significance F

Regression

7

1.98383E+12

2.83404E+11

110.4229

3.17667E-49

Residual

120

3.07984E+11

2566532218

Total

127

2.29181E+12

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

-12055.20512

44691.44115

-0.269743038

0.787821

-100541.1483

76430.74

-100541

76430.74

SqFt

274.4720171

28.71182947

9.559544697

1.93E-16

217.624593

331.3194

217.6246

331.3194

Bedrooms

24088.33576

7944.589907

3.032042691

0.002977

8358.600646

39818.07

8358.601

39818.07

Bathrooms

37363.03284

10792.47277

3.461952939

0.000744

15994.68785

58731.38

15994.69

58731.38

Offers

-40757.52654

5519.172415

-7.384717032

2.21E-11

-51685.10382

-29829.9

-51685.1

-29829.9

Brick Coded

85958.21519

10054.72173

8.549039696

4.7E-14

66050.56593

105865.9

66050.57

105865.9

East coded

-12020.22191

12314.42924

-0.976108732

0.330974

-36401.93479

12361.49

-36401.9

12361.49

west coded

99685.90872

15680.03715

6.357504628

3.86E-09

68640.52643

130731.3

68640.53

130731.3

(b)Consider Model 2 from Individual Assignment 2.Use this regression model to test (at the 5% level of significance) if the brick premium in the West exceeds the brick premium in the North.

Model 2 Output

State the null and alternative hypotheses.

State the p-value for this test.

State the statistical conclusion.

Communicate the results of the test in "plain English" within the context of the problem.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.934623672

R Square

0.873521408

Adjusted R Square

0.863874736

Standard Error

49562.93089

Observations

128

ANOVA

df

SS

MS

F

Significance F

Regression

9

2.00195E+12

2.22E+11

90.55158

1.01432E-48

Residual

118

2.89865E+11

2.46E+09

Total

127

2.29181E+12

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Intercept

-89.79829617

44216.901

-0.00203

0.998383

-87651.3003

87471.704

-87651.3

SqFt

276.8302333

28.2262254

9.807554

5.74E-17

220.9346225

332.72584

220.9346

Bedrooms

26192.77172

7825.496458

3.347107

0.001096

10696.15825

41689.385

10696.16

Bathrooms

30094.14158

10894.6699

2.762281

0.00666

8519.729105

51668.554

8519.729

Offers

-41398.0651

5412.84349

-7.64812

6.05E-12

-52116.96885

-30679.161

-52117

Brick Coded

60960.29572

20572.89716

2.963136

0.003684

20220.35839

101700.23

20220.36

East coded

-8085.045065

13899.72344

-0.58167

0.561899

-35610.28167

19440.192

-35610.3

west coded

81298.35221

16849.02308

4.825108

4.23E-06

47932.69938

114664.01

47932.7

Brick*East

9080.366235

25423.74171

0.357161

0.721609

-41265.56394

59426.296

-41265.6

Brick*west

61854.24045

26704.64404

2.316235

0.022271

8971.774935

114736.71

8971.775

(c) Consider Model 2 from Individual Assignment 2.Use this regression model to test (at the 5% level of significance) if the average increase in price for a 1 square foot increase in floor area is less than $300 per square foot.

State the null and alternative hypotheses.

Compute the test statistic.

Compute the p-value for this test.

State the Excel function (specifying all inputs) that will compute this probability.

State the statistical conclusion.

Communicate the results of the test in "plain English" within the context of the problem.

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