Introduction To Statistics And Data Analysis
6th Edition
ISBN: 9781337793612
Author: PECK, Roxy.
Publisher: Cengage Learning,
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Chapter 13.1, Problem 13E
- Consider the accompanying data on
x = Advertising share
and
y = Market share
for a particular brand of soft drink during 10 randomly selected years.
- a. Construct a
scatterplot for these data. Is the simple linear regression model appropriate for describing the relationship between x and y? - b. Calculate the equation of the estimated regression line and use it to obtain the predicted market share when the advertising share is 0.09.
- c. Calculate the value of r2. Interpret this value.
- d. Calculate a point estimate of σ. What value for degrees of freedom is associated with this estimate?
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Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy) and the independent variables are the age of the worker (Age), the number of years of education received (Edu), the number of years at the previous job (Job Yr), a dummy variable for marital status (Married:
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Working as a professor, I may want to try and predict success on a final exam by student success on exam 1 and see whether or not there is a relationship between those. I gather data from a set of students and obtain their first exam score and their final exam score. Using the following data, find the Pearson’s r correlation coefficient, produce a linear regression equation, and describe the associated R2 value.
First exam score (X)
Final exam score (Y)
95
100
90
92
95
90
85
90
85
85
80
75
65
75
60
50
70
82
90
95
80
100
90
90
75
60
75
80
Pearson’s r = ______________
Is the r significant? _______________
Linear regression equation: ____________________
Working as a professor, I may want to try and predict success on a final exam by student success on exam 1 and see whether or not there is a relationship between those. I gather data from a set of students and obtain their first exam score and their final exam score. Using the following data, find the Pearson’s r correlation coefficient, produce a linear regression equation, and describe the associated R2 value.
First exam score (X)
Final exam score (Y)
95
100
90
92
95
90
85
90
85
85
80
75
65
75
60
50
70
82
90
95
80
100
90
90
75
60
75
80
R2 = ____________________
What does R2 in this example mean? ____________________________________________
What would the final exam score be for someone who scored a 75 on the first exam?
_______________
What would the final exam score be for someone who scored a 90 on the first exam?
_______________
Chapter 13 Solutions
Introduction To Statistics And Data Analysis
Ch. 13.1 - Let x be the size of a house (in square feet) and...Ch. 13.1 - Consider the variables and population regression...Ch. 13.1 - The flow rate in a device used for air quality...Ch. 13.1 - The paper Predicting Yolk Height, Yolk Width,...Ch. 13.1 - A sample of small cars was selected, and the...Ch. 13.1 - Prob. 6ECh. 13.1 - Suppose that a simple linear regression model is...Ch. 13.1 - a. Explain the difference between the line y x...Ch. 13.1 - Prob. 9ECh. 13.1 - Hormone replacement therapy (HRT) is thought to...
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