Question: Regression Models Answer in word format. Question 1-40 Birth Length (in) of Newborn Infants Height of Mother (in) Height of Father (in) Birth Weight of
Regression Models
Answer in word format. Question 1-40
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 | 20.4 | 61 | 60 | 7.4 |
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 | 21.3 | 62 | 71 | 7.1 |
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 | 21.4 | 63 | 71 | 6.2 |
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 | 24.1 | 66 | 73 | 6.6 |
24 | 24.1 | 66 | 72 | 7.1 |
25 | 22.8 | 63 | 68 | 7.1 |
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 a newborn'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 a newborn'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 a newborn'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 a newborn'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 a newborn'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 a newborn'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 a newborn'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: Which of 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 |
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7 |
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