Graph the data and the best-fit line.yO15105у1510522N6 86 8101012X- X12хоу15105у1510522446 8 106 8101212XX Find the regression line associated with the set of points. (Round all coefficients to four decimal places.) HINT [See Example 2.](−1, 0), (2, 2), (7, 7)y(x) = 0.875x+0.875X

Given set of points is(-1,0)(2,2)(7,7)

Answered: Find the regression line associated…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section4.3: Fitting Linear Models To Data

Problem 7SE: A regression was run to determine whether there is arelationship between the diameter of a tree (x,...

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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?
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
A 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?
Life Expectancy The average life expectancy in the United States has been rising steadily over the past few decades, as shown in the table. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Use the linear model you found in part (b) to predict the life expectancy in the year 2006. (d) Search the Internet or your campus library to find the actual 2006 average life expectancy. Compare to your answer in part (c).
A 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=0.970
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
A regression was run to determine whether there isa relationship between hours of TV watched per day (x) and number of sit-ups a person can do (y). The results of the regression are given below. Use this topredict the number of situps a person who watches 11 hours of TV can do. y=ax+b a=1.341 b=32.234 r=0.896
Cellular Phone Subscribers The table shows the numbers of cellular phone subscribers y in millions in the United States from 2008 through 2013. Source: CTIA- The Wireless Association Year200820092010201120122013Number,y270286296316326336 (a) Find the least squares regression line for the data. Let x represent the year, with x=8 corresponding to 2008. (b) Use the linear regression capabilities of a graphing utility to find a linear model for the data. How does this model compare with the model obtained in part a? (c) Use the linear model to create a table of estimated values for y. Compare the estimated values with the actual data.

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Find the regression line associated with the set of points. (Round all coefficients to four decimal places.) HINT [See Example 2.] (-1,0), (2, 2), (7, 7) y(x) = 0.875x+0.875 X