Elementary Statistics: A Step-by-Step Approach with Formula Card
9th Edition
ISBN: 9780078136337
Author: Allan G. Bluman
Publisher: McGraw-Hill Education
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Chapter 10.2, Problem 22E
For Exercises 11 through 27, use the same data as for the corresponding exercises in Section 10–1. For each exercise, find the equation of the regression line and find the y′ value for the specified x value. Remember that no regression should be done when r is not significant.
22. Life Expectancies A random sample of nonindustrialized countries was selected, and the life expectancy in years is listed for both men and women.
Find women’s life expectancy in a country where men’s life expectancy = 60 years.
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Chapter 10 Solutions
Elementary Statistics: A Step-by-Step Approach with Formula Card
Ch. 10.1 - Stopping Distances In a study on speed control, it...Ch. 10.1 - What is meant by the statement that two variables...Ch. 10.1 - How is a linear relationship between two variables...Ch. 10.1 - What is the symbol for the sample correlation...Ch. 10.1 - What is the range of values for the correlation...Ch. 10.1 - What is meant when the relationship between the...Ch. 10.1 - Prob. 6ECh. 10.1 - What is the diagram of the independent and...Ch. 10.1 - What is the name of the correlation coefficient...Ch. 10.1 - What statistical test is used to test the...
Ch. 10.1 - When two variables are correlated, can the...Ch. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - Prob. 12ECh. 10.1 - Prob. 13ECh. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - Prob. 17ECh. 10.1 - Prob. 18ECh. 10.1 - Prob. 19ECh. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - Prob. 23ECh. 10.1 - For Exercises 11 through 27, perform the following...Ch. 10.1 - Prob. 25ECh. 10.1 - Prob. 26ECh. 10.1 - Prob. 27ECh. 10.1 - Prob. 28ECCh. 10.1 - Prob. 29ECCh. 10.1 - Prob. 30ECCh. 10.2 - Applying the Concepts 102 Stopping Distances...Ch. 10.2 - What two things should be done before one performs...Ch. 10.2 - What are the assumptions for regression analysis?Ch. 10.2 - Prob. 3ECh. 10.2 - What is the symbol for the slope? For the y...Ch. 10.2 - Prob. 5ECh. 10.2 - When all the points fall on the regression line,...Ch. 10.2 - What is the relationship between the sign of the...Ch. 10.2 - As the value of the correlation coefficient...Ch. 10.2 - Prob. 9ECh. 10.2 - When the value of r is not significant, what value...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - Prob. 12ECh. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - Prob. 17ECh. 10.2 - Prob. 18ECh. 10.2 - Prob. 19ECh. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - Prob. 25ECh. 10.2 - Prob. 26ECh. 10.2 - For Exercises 11 through 27, use the same data as...Ch. 10.2 - Prob. 28ECh. 10.2 - Prob. 29ECh. 10.2 - For Exercises 28 through 33, do a complete...Ch. 10.2 - For Exercises 28 through 33, do a complete...Ch. 10.2 - For Exercises 28 through 33, do a complete...Ch. 10.2 - Prob. 33ECh. 10.2 - For Exercises 34 and 35, do a complete regression...Ch. 10.2 - For Exercises 34 and 35, do a complete regression...Ch. 10.2 - For Exercises 13, 15, and 21 in Section 101, find...Ch. 10.2 - Prob. 37ECCh. 10.2 - The value of the correlation coefficient can also...Ch. 10.3 - Applying the Concepts 103 Interpreting Simple...Ch. 10.3 - What is meant by the explained variation? How is...Ch. 10.3 - What is meant by the unexplained variation? How is...Ch. 10.3 - What is meant by the total variation? How is it...Ch. 10.3 - Define the coefficient of determination.Ch. 10.3 - How is the coefficient of determination found?Ch. 10.3 - Define the coefficient of nondetermination.Ch. 10.3 - How is the coefficient of nondetermination found?Ch. 10.3 - Prob. 8ECh. 10.3 - Prob. 9ECh. 10.3 - Prob. 10ECh. 10.3 - Prob. 11ECh. 10.3 - Prob. 12ECh. 10.3 - Prob. 13ECh. 10.3 - Prob. 14ECh. 10.3 - Prob. 15ECh. 10.3 - Compute the standard error of the estimate for...Ch. 10.3 - Compute the standard error of the estimate for...Ch. 10.3 - Compute the standard error of the estimate for...Ch. 10.3 - Prob. 19ECh. 10.3 - For the data in Exercises 14 in Sections 101 and...Ch. 10.3 - Prob. 21ECh. 10.3 - Prob. 22ECh. 10.4 - Applying the Concepts 104 More Math Means More...Ch. 10.4 - Explain the similarities and differences between...Ch. 10.4 - What is the general form of the multiple...Ch. 10.4 - Prob. 3ECh. 10.4 - Prob. 4ECh. 10.4 - How do the values of the individual correlation...Ch. 10.4 - Age, GPA, and Income A researcher has determined...Ch. 10.4 - Prob. 7ECh. 10.4 - Prob. 8ECh. 10.4 - Aspects of Students Academic Behavior A college...Ch. 10.4 - Age, Cholesterol, and Sodium A medical researcher...Ch. 10.4 - Explain the meaning of the multiple correlation...Ch. 10.4 - What is the range of values R can assume?Ch. 10.4 - Prob. 13ECh. 10.4 - What are the hypotheses used to test the...Ch. 10.4 - What test is used to test the significance of R?Ch. 10.4 - What is the meaning of the adjusted R2? Why is it...Ch. 10 - Prob. 10.1.1RECh. 10 - For Exercises 1 through 7, do a complete...Ch. 10 - Prob. 10.1.3RECh. 10 - For Exercises 1 through 7, do a complete...Ch. 10 - For Exercises 1 through 7, do a complete...Ch. 10 - For Exercises 1 through 7, do a complete...Ch. 10 - Prob. 10.1.7RECh. 10 - For Exercise 4, find the standard error of the...Ch. 10 - Prob. 10.2.9RECh. 10 - Prob. 10.2.10RECh. 10 - Prob. 10.2.11RECh. 10 - Prob. 10.2.12RECh. 10 - (Opt.) A study found a significant relationship...Ch. 10 - Prob. 10.2.14RECh. 10 - Prob. 10.2.15RECh. 10 - Prob. 1DACh. 10 - Prob. 2DACh. 10 - Prob. 3DACh. 10 - Prob. 1CQCh. 10 - Determine whether each statement is true or false....Ch. 10 - Determine whether each statement is true or false....Ch. 10 - Determine whether each statement is true or false....Ch. 10 - Determine whether each statement is true or false....Ch. 10 - Determine whether each statement is true or false....Ch. 10 - Prob. 7CQCh. 10 - Select the best answer. 8. To test the...Ch. 10 - Select the best answer. 9. The test of...Ch. 10 - Prob. 10CQCh. 10 - Prob. 11CQCh. 10 - Prob. 12CQCh. 10 - Complete the following statements with the best...Ch. 10 - Prob. 14CQCh. 10 - Prob. 15CQCh. 10 - Prob. 16CQCh. 10 - Prob. 17CQCh. 10 - Prob. 18CQCh. 10 - Prob. 19CQCh. 10 - Prob. 20CQCh. 10 - Prob. 21CQCh. 10 - Prob. 22CQCh. 10 - Prob. 23CQCh. 10 - For Exercise 20, find the 90% prediction interval...Ch. 10 - Prob. 25CQCh. 10 - Prob. 26CQCh. 10 - (Opt.) Find R when ryx1 = 0.561 and ryx2 = 0.714...Ch. 10 - Prob. 28CQCh. 10 - Prob. 1CTCCh. 10 - Prob. 2CTCCh. 10 - Prob. 3CTCCh. 10 - Prob. 4CTCCh. 10 - Product Sales When the points in a scatter plot...Ch. 10 - Prob. 6CTCCh. 10 - Prob. 7CTCCh. 10 - Product Sales When the points in a scatter plot...Ch. 10 - Prob. 9CTC
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- Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forward
- Use the given information to find the coefficient of determination. 31) A regression equation is obtained for a collection of paired data. It is found that the total variation is 24.488, the explained variation is 15.405, and the unexplained variation is 9.083. Find the coefficient of determination.arrow_forwardSTER. 1. Wine Consumption. The table below gives the U.S. adult wine consumption, in gallons per person per year, for selected years from 1980 to 2005. a) Create a scatterplot for the data. Graph the scatterplot Year Wine below. Consumption 2.6 b) Determine what type of model is appropriate for the 1980 data. 1985 2.3 c) Use the appropriate regression on your calculator to find a Graph the regression equation in the same coordinate plane below. d) According to your model, in what year was wine consumption at a minimum? A e) Use your model to predict the wine consumption in 2008. 1990 2.0 1995 2.1 2000 2.5 2005 2.8arrow_forwardUse Data Set 7 found on my website for this question. Consider two models: Big and Small. Both models are predicting Exam Tot. Big uses four variables (Female?, Year, Time, and H Total) to predict Exam Tot. Small uses two variables (Time and H Total) to predict Exam Tot. Run a regression for each model. Which one is a better model? Small is better, but it's arguable that Big is better Clearly Big Both are equally good / It's hard to tell. Big is better, but it's arguable that Small is better Clearly Smallarrow_forward
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