# Homework Assignment

**Paper , Order, or Assignment Requirements**

Instructions for Homework Assignment: Use Excel to construct a spreadsheet for each of the four models (Scenario 1-7) then answer Question 40 based upon your calculations.

Birth Length (in) of Newborn Infants Height of Mother (in) Height of Father (in) Birth Weight of Nearest Sibling (lb)

1 22.0 61 70 6.5

2 23.5 64 72 6.1

3 24.0 64 74 7.3

4 24.7 59 71 5.8

5 18.7 59 60 5.9

6 22.1 64 62 6.7

7 23.0 62 73 6.8

8 24.3 64 76 7.2

9 22.3 66 74 5.9

10 22.1 65 72 6.1

11 20.3 63 71 6

12 24.2 64 76 7.4

13 21.9 65 72 6.2

14 23.4 62 78 6.7

15 26.1 64 77 7.1

16 22.5 63 72 6.8

17 21.1 61 73 6.5

18 22.6 63 69 6.7

19 21.9 63 68 6.2

20 19.6 60 61 5.9

21 19.6 61 64 5.8

22 22.5 64 66 6.2

23 21.6 65 73 6.5

24 24.1 66 72 7.1

25 22.8 63 68 7.1

After you have submitted your answers in the Assignment #_ Submission Link, upload the Excel file (provided you by the Instructor) containing your answers and calculations into the Home Work #_ Supporting Documentation Submission link prior to the due date and time. As stated in the syllabus a score of zero will be awarded for the assignment if this Excel file is not submitted.

Scenario: As a researcher studying how inherited traits influence newborn babies. You have gathered genetic data on newborns’, parents and sibling as shown in the table above.

Scenario 1: Perform a simple linear regression analysis to predict anewborn’s birth length (in inches) using the father’s height as a predictor variable. Conduct your analysis using a 95% level of confidence.

Question 1: Does the regression model confirm a correlation between the dependent variable and the independent variable? How do you know?(5 points)

Question 2: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence? How do you know?(5 points)

Question 3: Is the statistical significance of the linear relationship between the dependent and independent variable acceptable for a 95% level of confidence? How do you know?(5 points)

Question 4: What is the regression equation for the model?(5 points)

Question 5: What is the predicted birth length of a newborn whose father is 75.3 inches tall? (5 points)

Scenario 2: Perform a simple linear regression analysis to predict anewborn’s birth length (in inches) using the mother’s height as a predictor variable. Conduct your analysis using a 95% level of confidence.

Question 6: Does the regression model confirm a correlation between the dependent variable and the independent variable?How do you know? (5 points)

Question 7: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 8: Is the statistical significance of the linear relationship between the dependent and independent variable acceptable for a 95% level of confidence?How do you know?

Question 9: What is the regression equation for the model?(5 points)

Question 10: What is the predicted birth length of a newborn whose mother is 61.5 inches tall? (5 points)

Scenario 3: Perform a simple linear regression analysis to predict anewborn’s birth length (in inches) using the nearest (in age) sibling’s birth weight as a predictor variable. Conduct your analysis using a 95% level of confidence.

Question 11: Does the regression model confirm a correlation between the dependent variable and the independent variable?How do you know?(5 points)

Question 12: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 13: Is the statistical significance of the linear relationship between the dependent and independent variable acceptable for a 95% level of confidence?How do you know?(5 points)

Question 14: What is the regression equation for the model?(5 points)

Question 15: What is the predicted birth length of a newborn whose nearest sibling weighs 7.0 lbs.?(5 points)

Scenario 4: Perform a multiple linear regression analysis to predict anewborn’s birth length (in inches) using both the mother’s height (X1) and the father’s height (X2) as the predictor variables. Conduct your analysis using a 95% level of confidence.

Question 16: Does the regression model confirm a correlation between the dependent variable and the independent variables?How do you know?(5 points)

Question 17: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 18: What is the Critical Value of F associated with this regression model?

Question 19: What is the regression equation for the model?(5 points)

Question 20: Are both independent variables in this model significant? How do you know?(5 points)

Question 21: What is the predicted birth length of a newborn whose mother is 59.6 inches tall and the father’s height of 75.1 inches? (5 points)

Scenario 5: Perform a multiple linear regression analysis to predict anewborn’s birth length (in inches) using the father’s height (X1) and the birth weight of the nearest sibling (X2) as the predictor variables. Conduct your analysis using a 95% level of confidence.

Question 22: Does the regression model confirm a correlation between the dependent variable and the independent variables?How do you know?(5 points)

Question 23: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 24: What is the value of F associated with this regression model?(5 points)

Question 25: What is the regression equation for the model?(5 points)

Question 26: Are both independent variables in this model significant? How do you know?(5 points)

Question 27: What is the predicted birth length of a newborn whose father’s height of 73.6 inches tall and the nearest sibling’s birth weight is 6.25 lbs?(5 points)

Scenario 6: Perform a multiple linear regression analysis to predict anewborn’s birth length (in inches) using the mother’s height (X1), and the birth weight of the nearest sibling (X2) as the predictor variables. Conduct your analysis using a 95% level of confidence.

Question 28: Does the regression model confirm a correlation between the dependent variable and the independent variables?How do you know?(5 points)

Question 29: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 30: What is the value of F associated with this regression model?(5 points)

Question 31: What is the regression equation for the model?(5 points)

Question 32: Are all three independent variables in this model significant? How do you know?(5 points)

Question 33: What is the predicted birth length of a newborn whose mother’s height is 58.5 inches and the nearest sibling’s birth weight is 6.9 lbs?(5 points)

Scenario 7: Perform a multiple linear regression analysis to predict anewborn’s birth length (in inches) using the mother’s height (X1), the father’s height (X2) and the birth weight of the nearest sibling (X3) as the predictor variables. Conduct your analysis using a 95% level of confidence.

Question 34: Does the regression model confirm a correlation between the dependent variable and the independent variables?How do you know?(5 points)

Question 35: Is the statistical significance of the model as a whole acceptable for a 95% level of confidence?How do you know?(5 points)

Question 36: What is the value of F associated with this regression model?(5 points)

Question 37: What is the regression equation for the model?(5 points)

Question 38: Are all three independent variables in this model significant? How do you know?(5 points)

Question 39: What is the predicted birth length of a newborn whose mother’s height is 58.5 inches, a father’s height of 71.6 inches and the nearest sibling’s birth weight is 6.4 lbs?(5 points)

Question 40: Whichof the seven regression models is the preferred model, and why? This is not an “opinion” answer; please reference your data to validate your answer. (10 points)

The following table may help you organize your answers.

Scenario r r2 Adj. r2 Sig. F p-value p-value p-value

1

2

3

4

5

6

7

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