Question

In: Statistics and Probability

Calculate and interpret r. Calculate and interpret r2 Weight Fuel Efficiency Car1 3162 19 Car2 2566...

  1. Calculate and interpret r.

  1. Calculate and interpret r2

Weight

Fuel Efficiency

Car1

3162

19

Car2

2566

29

Car3

2785

25

Car4

3283

26

Car5

3496

20

Car6

1044

27

Car7

2100

14

Car8

2539

45

Car9

1082

36

Car10

3025

13

Car11

2187

43

Car12

2686

18

Car13

1059

20

Car14

961

22

Car15

1764

36

Car16

1394

38

Car17

2658

40

Car18

2110

37

Car19

1569

17

Car20

2701

24

Solutions

Expert Solution

Solution(a)
Coefficient correlation r can be calculated as
Coefficient correlation r = ((n*Xi*Yi)-(Xi*Yi))/sqrt(((n*Xi^2)-(Xi)^2))*((n*Yi^2)-(Yi)^2))
Here n = 20

Weight(X)

Fuel Efficiency(Y)

X^2

Y^2

XY

3162

19

9998244

361

60078

2566

29

6584356

841

74414

2785

25

7756225

625

69625

3283

26

10778089

676

85358

3496

20

12222016

400

69920

1044

27

1089936

729

28188

2100

14

4410000

196

29400

2539

45

6446521

2025

114255

1082

36

1170724

1296

38952

3025

13

9150625

169

39325

2187

43

4782969

1849

94041

2686

18

7214596

324

48348

1059

20

1121481

400

21180

961

22

923521

484

21142

1764

36

3111696

1296

63504

1394

38

1943236

1444

52972

2658

40

7064964

1600

106320

2110

37

4452100

1369

78070

1569

17

2461761

289

26673

2701

24

7295401

576

64824

44171

549

109978461

16949

1186589


Correlation coefficient r = ((20*1186589)-(44171*549))/sqrt(((20*109978461)-(44171*44171))*((20*16949)-(549*549))) = -518099/sqrt(248491979*37579) = -0.1695
Form the correlation coefficient r we can see that correlation coefficient is in negative that means both variables are negatively correlated with each other and both variables are very weakly correlated with each other.
Solution(b)
Coefficient of determination r^2 = (Coefficient correlation)^2 = (-0.1695)^2 = 0.0287
So r^2 or coefficient of determination tells us that this model explains 2.87% variation in dependent variable due to variation in independent variable.


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