Using the Instructor ranking data conduct a simple linear regression to predict a student’s scores based...
Using the Instructor ranking data conduct a simple linear regression to predict a student’s scores based on the number of hours the student studies and answer the following questions:
- What is the value of the intercept of this regression equation?
- What is the value of the slope of this regression equation and what is its interpretation within the context of this problem?
- Write the equation for this logistic regression model
- R2 = What does this number mean?
- F= Explain how F (F ratio) is calculated and what it means.
- Write the results in APA style.
| Class Participation | Actual grade | Hours Studying | gender |
| 1 | 98 | 5 | f |
| 2 | 94 | 5 | f |
| 3 | 88 | 4 | m |
| 4 | 91 | 4.5 | f |
| 5 | 93 | 4.1 | m |
| 6 | 88 | 3.8 | f |
| 7 | 88 | 3 | f |
| 8 | 85 | 3 | m |
| 9 | 82 | 3 | m |
| 10 | 66 | 2 | m |
| 11 | 71 | 1 | f |
| 12 | 61 | 1 | m |
Homework Answers
The intercept is 57.8939
The slope is 7.8749. It can be interpreted as for a unit change in Hours of Study Grade increases by 7.8749 units.
Since the response is not dichotomous we can't fit logistic regression model.
R2 = 0.8737 which can be interprered as 87.37℅ variation in Grade due to study hours is explained by model.
F cal = 69.1830
Which is rati of Meas square Regression to Mean square Residual. It given idea about significance of regression model.
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