Concept explainers
Reminder Round all the answers to two decimal places unless otherwise indicated.
Women Employed Outside the Home The following table shows the number, in millions, of women employed outside the home in the given year.
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a. Use regression to find a quadratic model for the data. (Round the regression parameters to three decimal places.)
b. Express using functional notation the number of women working outside the home in
c. The actual number of women working outside the home in
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FUNCTIONS+CHANGE -WEBASSIGN
- TEST YOUR UNDERSTANDING The following table shows the average price P, in dollars, of a gallon of regular gas t years after 2000. t = year since 2000 0 2 4 7 8 P = price in dollars 1.51 1.36 1.88 2.80 3.27 Find the equation of the regression line for P as a function of t. What price does your model give for gas in 2009? Compute your answer with the actual value of 2.35.arrow_forwardA regression was run to determine whether there is arelationship between the diameter of a tree (x, in inches) and the tree’s age (y, in years). Theresults of the regression are given below. Use this topredict the age of a tree with diameter 10 inches. y=ax+ba=6.301b=1.044r=0.970arrow_forwardRemainder Round all answers to two decimal places unless otherwise indicated. Cell Phones The following table gives the amount spent on cellular service worldwide, in trillions of U.S. dollars. Round the regression parameters to three decimal places. Date Cellular service revenue 2011 1.01 2012 1.05 2013 1.09 2014 1.11 a.Plot the data points. b.Find the equation of the regression line and add its graph to the plotted data. c.In 2015, 1.14 trillion was spent on cellular service. If you had been a financial strategist in 2014 with only the data in the table above available, what would been your prediction for the amount spent on cellular service in 2015?arrow_forward
- 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?arrow_forwardLife 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_forwardRemainder Round all answers to two decimal places unless otherwise indicated. Domestic Auto Sales in the United States For 2005 through 2008, the following table shows the total U.S. sales, in millions, of domestic automobiles excluding light trucks. Date Domestic cars sold 2005 5.53 2006 5.48 2007 5.25 2008 4.54 a.Get the equation of the regression line rounding parameters to two decimal places, and explain in practical terms the meaning of the slope. In particular, comment on the meaning of the sign of the slope. b.Plot the data points and the regression line. c.In 2009, 3.62 million domestic cars were sold in the United States. How does the forecast obtained from the regression line compare with this figure?arrow_forward
- Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00arrow_forwardA Dubious Model of Oil Prices The following table shows the prices of oil in U.S. dollars per barrel, t years since 1990, One analysis involving additional data used a cubic equation to model this data. t Years since 1990 0 2 5 7 10 12 15 17 20 21 P Price, dollars per barrel 18.91 16.22 16.63 18.20 27.04 23.47 49.63 69.04 77.46 106.92 a. Use cubic regression to model these data. Round the regression parameters to four decimal places. b. Plot the data along with the cubic model. c. In the analysis mentioned above, the graph is expanded through 2020. Expand the viewing window to show the model from 1990 to 2020. d. What estimate does the model give for oil prices in 2015? e. The actual price of oil in December of 2015 was about 35 per barrel. What basic principle in the use of models would be violated in relying on the estimate in part d?arrow_forwardRemainder Round all answers to two decimal places unless otherwise indicated. 6. iPhone Sales The following table shows unit sales of iPhones for the given year. t= years since 2010 0 1 2 3 I= units sold millions 8.70 16.24 37.04 47.79 a.Find the equation of the regression line. b.Plot the data and the regression line on the same coordinate axes. c.How many units sold does the regression line predict for 2016? d.Use the Internet to find the number of iPhones actually sold in 2016, and compare that number with your answer to part c.arrow_forward
- Stopping Distance The table below shows the average stopping distance D, in feet, for a car on dry pavement versus the speed S of the car, in miles per hour. S= speed mph 15 25 35 40 60 75 D = stopping distance feet 44 85 136 164 304 433 a Find a model of stopping distance as power function of speed. b If speed is doubled, how is stopping distance affected? c Plot the data and the power model on the same screen.arrow_forwardRemainder Round all answers to two decimal places unless otherwise indicated. Long Jump The following table shows the length, in meters, of the winning long jump in the Olympic Games for the indicated year. One meter is 39.37 inches. Year 1900 1904 1908 1912 Length 7.19 7.34 7.48 7.60 a.Find the equation of the regression that gives the length as a function of time. Round the regression line parameters to three decimal places. b.Explain in practical terms the meaning of the slope of the regression line. c.Plot the data points and the regression line. d.Would you expect the regression line formula to be a good model of the winning length over a long period of time? Be sure to explain your reasoning. e.There were no Olympic Games in 1916 because of World War I, but the winning long jump in the 1920 Olympic Games was 7.15 meters. Compare this with the value that the regression line model gives. Is the result consistent with your answer to part d?arrow_forwardSpecial Rounding Instructions For this exercise set, round all regression parameters to three decimal places, but round all other answers to two decimal places unless otherwise indicated. Household IncomeThe following table shows the median income, in thousands of dollars, of American families for 2003 through 2008. Year Incomethousands of dollars 2003 52.68 2004 54.06 2005 56.19 2006 58.41 2007 61.36 2008 61.52 a.Plot the data. b.Use exponential regression to construct an exponential model for the income data. c.What was the yearly percentage growth rate in median family income during this period? d.From 2003 through 2008, inflation was about 3 per year. Did median family income keep pace with inflation during this period?arrow_forward
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