MATH 399N Week 2 MyStatLab Homework Solutions: 9.1, 9.2, 9.3, 9.4
1. Question: 9.1.1 Two variables have a positive linear correlation. Does the dependent variable increase or decrease as the independent variable increases?
2. Question: 9.1.7 Discuss the difference between r and p.
3. Question: 9.1.15 Suppose the scatter plot shows the results of a survey of 43 randomly selected males ages 24 to 35. Using age as the explanatory variables, choose the appropriate description for the graph. Explain your reasoning.
4. Question: 9.1.19 Identify the explanatory variable and the response variable.
A teacher wants to determine if the amount of homework given to her students can be used to predict the student’s test scores.
5. Question: 9.2.2 Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
6. Question: 9.2.9 Match this description with a description below.
The y-value of a data point corresponding to xi
7. Question: 9.2.11 Match the description below with its symbols(s).
The mean of the y-values.
8. Question: 9.2.15 Match the regression equation ŷ = – 0.667x + 52.6 with the appropriate graph.
9. Question: 9.2.19-T Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below.
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10. Question: Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in million) for 6 beef hot dogs are shown in table below.
11. Question: 9.2.33 Use the data in the table below to complete parts (a) through (d).
12. Question: 9.3.7 Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = 0.19412. Question: 9.3.7 Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = 0.194
13. Question: 9.3.9 Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = 0.988
14. Question: 9.4.1 The equation used to predict college GPA (range 0-4.0) is ŷ = 0.15 + 0.53×1 + 0,002×2, where x1 is high school GPA (range 0-4.0) and x2 is college board score (range 200-800). Use the multiple regression equation to predict college GPA for a high school GPA of 3.8 and a college board score of 400.
15. Question: 9.4.3 The equation used to predict the total body weight (in pounds) of a female athlete of a certain school is ŷ = – 112 + 3.55×1 + 1.72×2, where x1 is the female athlete’s height (in inches) and x2 is the female athlete’s percent body fat., measured as x2 %. Use the multiple regression equation to predict the total body weight for a female athlete who is 62 inches tall and has 16 % body fat.
