Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 7 15 9 13 10 12 5 y 11.17 18.13 14.88 18.37 16.25 17.99 14 6.13 18.41 17.28 11 6 8.81 8 13.19 y = ŷx + x (Round to two decimal places as needed.) ...

Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 7 15 9 13 10 12 5 y 11.17 18.13 14.88 18.37 16.25 17.99 14 6.13 18.41 17.28 11 6 8.81 8 13.19 y = ŷx + x (Round to two decimal places as needed.) ...

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

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XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. 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 the stock price to be in January 2012? January 2013?
Olympic 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?
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?2300
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
For 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.
For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line.x6111310941281457 y9.5715.8916.1115.2814.354.7316.1713.0815.737.3111.49Question content area bottomPart 1y=enter your response here+enter your response herex (Round to two decimal places as needed.)Part 2Create a scatterplot of the data. Choose the correct graph below. A.05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows: (4, 4.5); (5, 7.5); (6, 9.5); (7, 11.5); (8, 13); (9, 14.5); (10, 15.5); (11, 16); (12, 16); (13, 16); (14, 15.5).B.05101520250510152025xy A scatterplot has a horizontal x-scale from 0 to 25 in intervals of 1 and a vertical y-scale from 0 to 25 in intervals of 1. Eleven points are plotted with approximate coordinates as follows: (4, 7);…
The data below are the average one-way commute times (in minutes) for selected students and the number of absences for those students during the term. Find the equation of the regression line for the given data. What would be the predicted number of absences if the commute time was 95 minutes? Is this a reasonable question? Round the predicted number of absences to the nearest whole number. Round the regression line values to the nearest hundredth. Commute time (min), x Number of absences, v 72 | 85 91 90 Ss 98 75 100 80 3 10 10 15 4 15 O v = 0.45x - 30.27; 12 absences; No, it is not reasonable. 95 minutes is well outside the scope of the model. O v = 0.45x + 30.27; 73 absences; No, it is not reasonable. 95 minutes is well outside the scope of the model. O y = 0.45x - 30.27; 12 absences; Yes, it is reasonable. O y = 0.45x + 30.27; 73 absences; Yes, it is reasonable. %3D
The data below are the average one-way commute times (in minutes) for selected students and the number of absences for those students during the term. Find the equation of the regression line for the given data. What would be the predicted number of absences if the commute time was 95 minutes? Is this a reasonable question? Round the predicted number of absences to the nearest whole number. Round the regression line values to the nearest hundredth. Commute time (min), x 72 85 91 90 88 98 75 100 80 3 7 10 10 8 15 4 15 5 Number of absences, y O A. y=0 45x + 30 27, 73 absences; Yes, it is reasonable. O B. y=0.45x-30.27; 12 absences; No, it is not reasonable. Ninety-five minutes is well outside the scope of the model. O C. =0 45x + 30 27; 73 absences; No, it is not reasonable. Ninety-five minutes is well outside the scope of the model, OD. y 0 45x-30 27; 12 absences; Yes, it is reasonable. O Time Remaining: 01.55 29 Next 110 insert prt sc esc & 7 + backspac %23 3 %24 4 5. P Q W R T tab 00…
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 table shows the shoe size and heights (in.) for 6 men. Shoe size, x Height, y 8.0 66.0 8.5 68.0 12.0 74.0 12.5 73.0 10.5 11.5 73.0 70.0 Find the regression equation. (Round to three decimal places as needed.) Choose the correct graph below. O A. OB. OC. OD. 75- 75- 65 13 13 Shoe size Shoe size Shoe size Shoe size Height (in.) Height (in.)