Calculate the regression equation of X on Y from the data given below, taking deviationsfrom actual means of X and Y.121415141817424045473945Estimate the likely demand when the X = 25.

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Answered: Calculate the regression equation of X…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4PPS

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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?
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?
What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
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
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
10) A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
A statistics student wanted to determine if the distance to a destination was related to the price an airline would charge to fly to that destination. The student did a regression of airfare, y, on distance, x, and obtained the printout shown below from a statistical software package. Predictor Coef Constant 83.02 Distance 0.117 Oŷ= 0.117+83.02x Oy=83.02 +0.117x Oy= 49.29 + 83.02x Oŷ= 0.028 + 0.117x Oy=83.02 + 25.25x 1 SE Coef 49.29 0.028 S = 25.25 R-Sq = 63.2 % Which of the following is the correct equation of the least-squares line? Mark this and return t-ratio 1.689 4.179 R-Sq (Adj) = 64.7% Save and Exit р 0.046 0.000 di I tv Next AM Submit Aa
A regression was run to determine if there is a relationship between hours of study per week (z) and the test scores (y)- The results of the regression were: y=ax+b a=5.701 b=31.89 r2=0.660969 r=0.813 Use this to predict the final exam score of a student who studies 3.5 hours per week, and please round your answer to a whole number. Question Help: Message instructor Submit Question rse here to search R
Regression analysis was applied between sales data (y) and advertising data (x) and the following information was obtained. SSR = 800SST = 1250Sample Size (n) = 12 The standard error of the estimate is
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.853 b=34.041 r2=0.389376 r=-0.624 Use this to predict the number of situps a person who watches 7 hour(s) of TV can do, and please round your answer to a whole number.
Nine data points of data yield r=0.867 and the regression equation y=19.4+0.93x. Also, y=64.7. What is the best predicted value of y for x=40?
For each gender, estimate an earnings regression where the dependent variable is Annual Earnings and the independent variable is Age. Report the results for each regression, and provide an interpretation of the coefficient associated with age. Female- annual earning: 49347.58 age: 42.81 education: 14.4 Male- Annual earning: 69984.54 age: 42.86 education: 14.11.

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Calculate the regression equation of X on Y from the data given below, taking deviations from actual means of X and Y. 12 14 15 14 18 17 42 40 45 47 39 45 Estimate the likely demand when the X 25.