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R.R. Jha, Bachelor's Degree

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Solve for the predicted values of y and the residuals for the

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Solve for the predicted values of y and the residuals for the following data. Comment on the size of the residuals.

Business Bankruptcies (1000) Firm Births (10,000) 34.3 58.1

35.0 55.4 38.5 57.0 40.1 58.5 35.5 57.4

37.9 58.0

Do not round the intermediate values. Round your answers to 4 decimal places, the tolerance is +/-0.0005.

x y Predicted () Residuals () 58.1 34.3 55.4 35.0 57.0 38.5 58.5 40.1 57.4 35.5 58.0 37.9

The residual for x = 58.1 is relatively largesmall, but the residual for x = 55.4 is quite largesmall

Can the annual new orders for manufacturing in the United States be predicted by the raw steel production in the United States? Shown on the next page are the annual new orders for 10 years according to the U.S. Census Bureau and the raw steel production for the same 10 years as published by the American Iron & Steel Institute. Use these data to develop a regression model to predict annual new orders by raw steel production. Construct a scatter plot and draw the regression line through the points.

Raw Steel Production (100,000s of net tons) New Orders ($ trillions) 99.9 2.74 97.9 2.87 98.9 2.93 87.9 2.87 92.9 2.98

Thanks for asking me, but I was away from my computer, just came online. Please let me know if you still need helpl with this one, or if you've other questions.

Okay. Then please post the question in image format. Tables aren't quite clear. Just take the screenshot of the question, save it, then attach the image using clip icon second right of the smiley icon.

Solve for the predicted values of y and the residuals for the following data. Comment on the size of the residuals.

Business Bankruptcies (1000)

Firm Births (10,000)

34.3

58.1

35.0

55.4

38.5

57.0

40.1

58.5

35.5

57.4

37.9

58.0

Do not round the intermediate values. Round your answers to 4 decimal places, the tolerance is +/-0.0005.

x

y

Predicted ( )

Residuals ()

58.1

34.3

55.4

35.0

57.0

38.5

58.5

40.1

57.4

35.5

58.0

37.9

The residual for x = 58.1 is relatively largesmall, but the residual for x = 55.

Can the annual new orders for manufacturing in the United States be predicted by the raw steel production in the United States? Shown on the next page are the annual new orders for 10 years according to the U.S. Census Bureau and the raw steel production for the same 10 years as published by the American Iron & Steel Institute. Use these data to develop a regression model to predict annual new orders by raw steel production. Construct a scatter plot and draw the regression line through the points.

Raw Steel Production (100,000s of net tons)

New Orders ($ trillions)

99.9

2.74

97.9

2.87

98.9

2.93

87.9

2.87

92.9

2.98

97.9

3.09

100.6

3.36

104.9

3.61

105.3

3.75

108.6

3.95

Do not round the intermediate values. Round your answers to 5 decimal places, the tolerance is +/-0.00005.

Can the annual new orders for manufacturing in the United States be predicted by the raw steel production in the United States? Shown on the next page are the annual new orders for 10 years according to the U.S. Census Bureau and the raw steel production for the same 10 years as published by the American Iron & Steel Institute. Use these data to develop a regression model to predict annual new orders by raw steel production. Construct a scatter plot and draw the regression line through the points.

Raw Steel Production (100,000s of net tons)

New Orders ($ trillions)

99.9

2.74

97.9

2.87

98.9

2.93

87.9

2.87

92.9

2.98

97.9

3.09

100.6

3.36

104.9

3.61

105.3

3.75

108.6

3.95

Do not round the intermediate values. Round your answers to 5 decimal places, the tolerance is +/-0.00005.