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.) ...
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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 accuracyFor 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?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 8 12 7 3 6 13 11 10 5 4 9 y 9.58 9.54 8.70 1.64 7.46 8.64 10.08 10.26 5.88 3.94 10.10 y=_+_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. 8 3 11 10 4 13 12 6 7 y 10.85 3.23 11.47 11.59 5.41 10.23 7.27 11.01 8.79 11.38 9.98 y =+x (Round to two decimal places as needed.) %3D Create a scatterplot of the data. Choose the correct graph below. O A. O B. OC. O D. Ay 25- Ay 25- 25- 25- 20- 20- 20- 20- 15 15 15- 15- 10 0 10 10 10 5 0 53 53 5- 0- 05 40 15 20 25 05 10 15 20 25 0 5 10 15 20 25 05 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. O A. There is no trend in the data. O B. There is an influential point that strongly affects the graph of the regression line. C. The data has a pattern that is not a straight line. D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s). MacBook Pro esc O00 O00 888 % & 4. 6 8. E Y. G H. P K. 5 F. %24 #3
- 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. 9 11 7 8 6 12 13 4 10 y 11.75 12.24 10.15 11.10 3.61 8.94 12.06 11.61 5.66 7.44 12.14 y =+ x (Round to two decimal places as needed.) %3D Create a scatterplot of the data. Choose the correct graph below. OA. В. OC. O D. 25- Ay 25- 25- 25- 20- 20- 203 20 15 15 155 15 o0000000000 53 103 10 0 105 105 5 5- 53 05 10 15 20 25 0- 05 10 15 20 25 0 5 10 15 20 25 05 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. A. There is no trend in the data. O B. The data has a pattern that is not a staight line. OC. There is an influential point that strongly affects the graph of the regression line. O D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s).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 9. 14 11 10 15 6 7 8 12 13 у 14.75 18.16 16.95 16.00 18.01 7.01 9.36 11.44 13.24 17.64 18.04 .... y = |x (Round to two decimal places as needed.) + Create a scatterplot of the data. Choose the correct graph below. O A. В. C. D. Ay 25- Ay 25- 25- 25- 204 20- 204 20- Q 15- 15- 15- 155 10- 105 10- 10= 5- 5- 55 X 07 0- 04 0- 10 15 20 25 10 15 20 25 5 10 15 20 25 5 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. A. There is no trend in the data. B. There is an influential point that strongly affects the graph of the regression line. C. The data has a pattern that is not a straight line. O D. There is no characteristic of the data that is ignored by the regression line.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 y11 19.8110 18.8714 20.826 12.067 14.214 6.8213 20.7912 20.465 9.599 17.628 16.07 y=__+__x create a scatterplot of the data. identify the characteristics of the data that is ignored by the regression line