Understandable Statistics: Concepts and Methods
12th Edition
ISBN: 9781337119917
Author: Charles Henry Brase, Corrinne Pellillo Brase
Publisher: Cengage Learning
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Textbook Question
Chapter 9.4, Problem 3P
For Problems 3-6, use appropriate multiple regression software of your choice and enter the data. Note that the data are also available for download at the Companion Sites for this text.
3. Medical: Blood Pressure The systolic blood pressure of individuals is thought to be related to both age and weight. For a random sample of 11 men, the following data were obtained:
- (a) Generate summary statistics, including the
mean and standard deviation of each variable. Compute the coefficient of variation (see Section 3.2) for each variable. Relative to its mean, which variable has the greatest spread of data values? Which variable has the smallest spread of data values relative to its mean? - (b) For each pair of variables, generate the sample
correlation coefficient r. Compute the corresponding coefficient of determination r2. Which variable (other than x1) has the greatest influence (by itself) on x1? Would you say that both variables x2 and x3 show a strong influence on x1? Explain your answer. What percent of the variation in x1 can be explained by the corresponding variation in x2? Answer the same question for x3. - (c) Perform a
regression analysis with x1 as the response variable. Use x2 and x3 as explanatory variables. Look at the coefficient of multiple determination. What percentage of the variation in x1 can be explained by the corresponding variations in x3 and x3 taken together? - (d) Look at the coefficients of the regression equation. Write out the regression equation. Explain how each coefficient can be thought of as a slope. If age were held fixed, but a person put on 10 pounds, what would you expect for the corresponding change in systolic blood pressure? If a person kept the same weight but got 10 years older, what would you expect for the corresponding change in systolic blood pressure?
- (e) Test each coefficient to determine if it is zero or not zero. Use level of significance 5%. Why would the outcome of each test help us determine whether or not a given variable should be used in the regression model?
- (f) Find a 90% confidence interval for each coefficient.
- (g) Suppose Michael is 68 years old and weighs 192 pounds. Predict his systolic blood pressure, and find a 90% confidence
range for your prediction (if your software produces prediction intervals).
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Use the dataset in Table 2 to answer the questions. The table shows the ages (in years) of seven children and the number of words in their vocabulary. For problems 9-12, use the regression equation found in question 7 to predict the value of for the values of given in each question unless it is not meaningful. If it is not meaningful to predict the value of for the -value, explain why not.
Table 2. Vocabulary
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3
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7. What is the equation of the regression line?
8. Construct a scatter plot for the data showing the regression line on the same graph.
For problems 9-12, see the instructions above.
9. x=2years
10. x=3years
11. x=6years
12. x=12years
Question 3.
Calculate and interpret the regression line for the data.
A manager wishes to determine the relationship between the number of years her sales representatives have been employed by the firm and their amount of sales (in thousands of dollars) per month. Find the equation of the regression line for the given data.
Chapter 9 Solutions
Understandable Statistics: Concepts and Methods
Ch. 9.1 - Statistical Literacy When drawing a scatter...Ch. 9.1 - Prob. 2PCh. 9.1 - Prob. 3PCh. 9.1 - Prob. 4PCh. 9.1 - Prob. 5PCh. 9.1 - Prob. 6PCh. 9.1 - Prob. 7PCh. 9.1 - Prob. 8PCh. 9.1 - Prob. 9PCh. 9.1 - Critical Thinking: Lurking Variables Over the past...
Ch. 9.1 - Prob. 11PCh. 9.1 - Prob. 12PCh. 9.1 - Prob. 13PCh. 9.1 - Health Insurance: Administrative Cost The...Ch. 9.1 - Prob. 15PCh. 9.1 - Geology: Earthquakes Is the magnitude of an...Ch. 9.1 - Prob. 17PCh. 9.1 - Prob. 18PCh. 9.1 - Prob. 19PCh. 9.1 - Prob. 20PCh. 9.1 - Prob. 21PCh. 9.1 - Prob. 22PCh. 9.1 - Prob. 23PCh. 9.1 - Prob. 24PCh. 9.2 - Statistical Literacy In the least-squares line...Ch. 9.2 - Prob. 2PCh. 9.2 - Critical Thinking When we use a least-squares line...Ch. 9.2 - Prob. 4PCh. 9.2 - Prob. 5PCh. 9.2 - Critical Thinking: Interpreting Computer Printouts...Ch. 9.2 - Prob. 7PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 9PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 11PCh. 9.2 - Prob. 12PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 14PCh. 9.2 - Prob. 15PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 17PCh. 9.2 - Prob. 18PCh. 9.2 - Prob. 19PCh. 9.2 - Residual Plot: Miles per Gallon Consider the data...Ch. 9.2 - Prob. 21PCh. 9.2 - Prob. 22PCh. 9.2 - Prob. 23PCh. 9.2 - Prob. 24PCh. 9.2 - Prob. 25PCh. 9.3 - Prob. 1PCh. 9.3 - Prob. 2PCh. 9.3 - Prob. 3PCh. 9.3 - Prob. 4PCh. 9.3 - Prob. 5PCh. 9.3 - Prob. 6PCh. 9.3 - Prob. 7PCh. 9.3 - In Problems 712, parts (a) and (b) relate to...Ch. 9.3 - Prob. 9PCh. 9.3 - Prob. 10PCh. 9.3 - In Problems 712, parts (a) and (b) relate to...Ch. 9.3 - Prob. 12PCh. 9.3 - Prob. 13PCh. 9.3 - Prob. 14PCh. 9.3 - Prob. 15PCh. 9.3 - Expand Your Knowledge: Time Series and Serial...Ch. 9.3 - Prob. 17PCh. 9.4 - Statistical Literacy Given the linear regression...Ch. 9.4 - Prob. 2PCh. 9.4 - For Problems 3-6, use appropriate multiple...Ch. 9.4 - For Problems 3-6, use appropriate multiple...Ch. 9.4 - Prob. 5PCh. 9.4 - Prob. 6PCh. 9 - Prob. 1CRPCh. 9 - Prob. 2CRPCh. 9 - Prob. 3CRPCh. 9 - Prob. 4CRPCh. 9 - Prob. 5CRPCh. 9 - Prob. 6CRPCh. 9 - Prob. 7CRPCh. 9 - Prob. 8CRPCh. 9 - Prob. 9CRPCh. 9 - Prob. 10CRPCh. 9 - Prob. 1DHCh. 9 - Prob. 1LCCh. 9 - Prob. 1UTCh. 9 - Prob. 2UTCh. 9 - Prob. 3UTCh. 9 - Prob. 4UTCh. 9 - Prob. 5UTCh. 9 - Prob. 6UTCh. 9 - Prob. 7UTCh. 9 - In Problems 16, please use the following steps (i)...Ch. 9 - Prob. 2CURPCh. 9 - Prob. 3CURPCh. 9 - Prob. 4CURPCh. 9 - Prob. 5CURPCh. 9 - Prob. 6CURPCh. 9 - Prob. 8CURPCh. 9 - Linear Regression: Blood Glucose Let x be a random...
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