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Engineering Probability and Inference Homework 5 In an article “Reactions on Painted Steel Under the Influence of Sodium Chloride, and Combinations Thereof”, measurements were taken of the Sodium Chloride deposition rate and steel weight loss

Statistics Dec 09, 2021

Engineering Probability and Inference Homework 5

  1. In an article “Reactions on Painted Steel Under the Influence of Sodium Chloride, and Combinations Thereof”, measurements were taken of the Sodium Chloride deposition rate and steel weight loss.

 

Sodium Chloride, x

14

18

40

43

45

112

Steel Weight Loss, y

280

350

470

500

560

1200

 

  1. Find the least-squares regression line relating the steel weight loss to the sodium chloride deposition rate.
  2. Do the data provide sufficient evidence to indicate that β1 is not 0? Use a significance level of 0.05.
  3. Find a 95% confidence interval for β1.
  4.  Find a 95% prediction interval for the amount of steel weight loss when the sodium chloride deposition rate is 50.
  5.  Find the correlation coefficient for this data.
  6. Do the data provide sufficient evidence to show there is a correlation between sodium chloride deposition and steel weight loss? Use a significance level of 0.05.
  7. Find the proportion of the variability in steel weight loss that is explained by the linear relationship with sodium chloride deposition rate (ie the coefficient of determination).

 

 

 

 

  1.  A political scientist wished to examine the relationship between voter image of a candidate and distance (in miles) between the residences of the voter and the candidate.

 

Rating

12

7

5

19

17

12

9

18

3

8

15

4

Distance

75

200

300

15

180

240

120

60

230

165

130

130

 

Calculate Spearman’s rank correlation coefficient.

 

 

 

 

  1. Suppose we want to predict job performance of Chevy mechanics based on mechanical aptitude test scores and test scores from personality test that measures conscientiousness. Use the data below:

 

Apt Test (X1)

40

45

38

50

48

55

53

55

58

40

Pers Test (X2)

25

20

30

30

28

30

34

36

32

34

Job Performance (Y)

1

2

1

3

2

3

3

4

4

3

 

Apt Test (X1)

55

48

45

55

60

60

60

65

50

58

Pers Test (X2)

38

28

30

36

34

38

42

38

34

38

Job Performance (Y)

5

3

3

2

4

5

5

5

4

3

 

 

 

  1. Set up the three normal equations needed to find the multiple regression model. Solve for the betas and give the multiple regression equation.
  2. Using the data given below, complete the ANOVA table for this data.

 

Source

df

SS

MS

F

Regression

 

19.96

 

 

Residual

 

 

 

 

Total

19

29.75

 

 

 

 

  1. What is the coefficient of determination for this data and what does it mean?

 

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