Consider the following data.3060901201503.15.87.99.49.79.9Usa technology to find a logistic regression curve y=1+ Abapproximating the given data. (Round o to 3 significant digits and A and N to 2 significant digits.) HINT (See Example 2.y%3=X Your answer cannot be understood or graded, More InformationDraw a graph showing the data points and regression curve.y1212101025507510012515020406080100125150y121210106f412255075100125150255075100125150

Construct the table as follows-

30 60 90 120 150 7.9 A. 3.1 Usa technology to find a logistic regression curve y- 9.4 9.7 9.9 approximating the given data. (Round b to 3 significant digits and A and N to 2 significant digits.) H 1+ Ab x Your answer cannot be understood or graded, More Information Draw a graph showing the data points and regression curve. y 12 12 10 10 41 21 25 50 75 100 125 150 20 40 60 100 125 130 12 12 10 10 41 21 25 50 75 100 125 150 50 75 100 125 150

30 60 90 120 150 7.9 A. 3.1 Usa technology to find a logistic regression curve y- 9.4 9.7 9.9 approximating the given data. (Round b to 3 significant digits and A and N to 2 significant digits.) H 1+ Ab x Your answer cannot be understood or graded, More Information Draw a graph showing the data points and regression curve. y 12 12 10 10 41 21 25 50 75 100 125 150 20 40 60 100 125 130 12 12 10 10 41 21 25 50 75 100 125 150 50 75 100 125 150

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

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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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?
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.
Cable TV The following table shows the number C. in millions, of basic subscribers to cable TV in the indicated year These data are from the Statistical Abstract of the United States. Year 1975 1980 1985 1990 1995 2000 C 9.8 17.5 35.4 50.5 60.6 60.6 a. Use regression to find a logistic model for these data. b. By what annual percentage would you expect the number of cable subscribers to grow in the absence of limiting factors? c. The estimated number of subscribers in 2005 was 65.3million. What light does this shed on the model you found in part a?
Special 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. Cost of Scientific periodicals The table below shows the average cost C, in dollars, of chemistry and physics periodicals tyears after 1980. 29 t=yearssince1980 C=cost,indollars 0 140 5 250 10 410 15 780 20 1300 22 1520 a.Make an exponential model of C as a function of t. b.Plot the data and the exponential model. c.What was the yearly percentage growth rate of the cost of chemistry and physics periodicals? d.If this exponential trend continues, what will be the expected average cost of physics and chemistry periodicals in 2020? Round your answer to the nearest dollar.
Special 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. Rare Coins The table below shows the estimated value C, in dollars, of an 1877 Indian Head Cent Philadelphia mint mark in very fine condition t years after 1950. t=time,inyearssince1950 C=value,indollars 0 25 30 400 45 625 54 1750 60 2000 a.Use exponential regression to model C as an exponential function of t. b.According to your exponential model, by what percentage does the value of the 1877 cent increase from year to year?
Special Rounding Instructions When you perform logistic regression, round the r value to three decimal places and the other parameters to two decimal places. Round all answers to two decimal places unless other-wise indicated. Fluorescent Bulbs Compact fluorescent light bulbs save energy when compared with traditional incandescent bulbs. Our green energy campaign includes efforts to get local residents to exchange their incandescent bulbs fur fluorescent bulbs. Initially 200 households make the change. Market studies suggest that, in the absence of limiting factors, we could increase that number by 25 each month. In our target area, there are 250,000 households, which we take as the limiting value. Make a logistic model that gives the number of households converting to fluorescent bulbs after t months.
The following table is adapted from a paramecium culture experiment conducted by Gause in 1934. The data show the paramecium population N as a function of time t in days. Use regression to find a logistic model for this population using a graphing calculator. Round the r value to three decimal places and the other parameters to two decimal places. t N 2 24 3 35 5 95 6 193 8 350 9 428 10 520 11 580 a) N = 83.54 / 1+680.87e^-0.558t b) N = 681.87 / 1+83.54e^-0.558t c) N = 680.87 / 1+83.54e^-0.558t d) N = 83.54 / 1+0.558e^-0.558t
*Based on the regression results, answer the following questions* A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEOs, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for the year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the null and alternative hypothesis that Excel is testing in reporting the tstats above? g) What is the…
*Based on the regression results, answer the following questions* A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEOs, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for the year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions h) Is there a significant amount of evidence (say at the 10% level of significance) that CEO’s make at least $2 million more than non-CEO’s? i) Suppose you’re not sure if all the variables above should be included in the regression.…
** Based on the regression results, answer the following questions ** A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEO’s, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions b) What is the estimated regression equation? c) What percentage of the variation in income in explained by the regressors? d) What is the standard error of the error term in the regression equation?
Consider the following sample regressions for the linear and the logarithmic models. Linear Logarithmic Intercept 6.7904 −5.6712 x 1.0607 NA In(x) NA 10.5447 * se 2.4935 1.5231 R2 0.8233 0.9341 Adjusted R2 0.8013 0.9259 b. Use the selected model to predict y for x = 10. (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) predicted y=