Country Consumption per capita Paper Consumptions (kg/1000 people) Fish consumption (kg) Oil consumption 1000 barrels/day Japan 19700 76892 158.7 5454 Portugal 5570 24126 132.7 277 United States 16500 84579 47 17033 Venezuela 2090 6860 31.1 430 Greece 4490 15641 42.1 331 Italy 10790 43098 44.3 1936 Norway 13400 41575 90.6 183 United Kingdom 9040 52355 43.9 1803 Philippines 640 940 76.3 235 Based on these data, multiple regression model equations can be obtained to predict per capita consumption which is influenced by paper consumption, fish consumption and fuel oil consumption. From Microsoft Excel processing, the following data are obtained:       a. How strong is the relationship! b. What is the coefficient of determination! c. How is the hypothesis test (H0 and alternative hypothesis) of the model whole!

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Country

Consumption per capita

Paper Consumptions (kg/1000 people)

Fish consumption

(kg)

Oil consumption

1000 barrels/day

Japan

19700

76892

158.7

5454

Portugal

5570

24126

132.7

277

United States

16500

84579

47

17033

Venezuela

2090

6860

31.1

430

Greece

4490

15641

42.1

331

Italy

10790

43098

44.3

1936

Norway

13400

41575

90.6

183

United Kingdom

9040

52355

43.9

1803

Philippines

640

940

76.3

235

Based on these data, multiple regression model equations can be obtained to predict per capita consumption which is influenced by paper consumption, fish consumption and fuel oil consumption. From Microsoft Excel processing, the following data are obtained:

 
 
 
a. How strong is the relationship!
b. What is the coefficient of determination!
c. How is the hypothesis test (H0 and alternative hypothesis) of the model whole!
OUTPUT
Regression Statistics
Multiple R
0,9677869
R Square
0,9366114
Adjusted R Square
0,8985783
Standard Error
2084,9394
Observations
9
ANOVA
Significance
df
SS
MS
F
F
Regression
321148160,6 107049387 24,62619 0,002013655
Residual
21734861,62
4346972,3
Total
8
342883022,2
Standard
Upper
Coefficients
Error
t Stat
P-value
Lower 95%
95%
-538,2796
1556,378436
0,3458539
0,74352
-4539,07774 3462,5185
Intercept
X Variable 1
X Variable 2
0,2336803
0,04397761
5,3136194
0,00315
0,12063223
0,3467283
18,087993
18,48045874
0,9787632
0,37264
-29,4175389
65,593524
X Variable 3
-0,211649
0,228690877
0,9254819
0,39718
-0,79951787
0,3762193
Transcribed Image Text:OUTPUT Regression Statistics Multiple R 0,9677869 R Square 0,9366114 Adjusted R Square 0,8985783 Standard Error 2084,9394 Observations 9 ANOVA Significance df SS MS F F Regression 321148160,6 107049387 24,62619 0,002013655 Residual 21734861,62 4346972,3 Total 8 342883022,2 Standard Upper Coefficients Error t Stat P-value Lower 95% 95% -538,2796 1556,378436 0,3458539 0,74352 -4539,07774 3462,5185 Intercept X Variable 1 X Variable 2 0,2336803 0,04397761 5,3136194 0,00315 0,12063223 0,3467283 18,087993 18,48045874 0,9787632 0,37264 -29,4175389 65,593524 X Variable 3 -0,211649 0,228690877 0,9254819 0,39718 -0,79951787 0,3762193
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