The table below lists the height h (in cm), the age a (in years), the gender g (1="Male", 0="Female"), and the weight w (in kg) of some college studentsAge Gender Weight8378554862We wish to fit a linear function of the formHeight181176164156169C₁=C₂=9=5822821to these data. Find the best approximation of this form, using least squares.Co-202011000f(t)=co+ch+c₂a +cag

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Answered: The table below lists the height h (in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following data were collected in an experiment to study the relationship between extrusion pressure (in KPa) and wear (in mg). | 150 175 200 225 250 275 10.4 12.4 14.9 15.0 13.9 11.9 y The least-squares quadratic model is y = -32.445714 + 0.43154286x – 0.000982857x². Using this equation, compute the residuals. b. Compute the error sum of squares SSE and the total sum of squares SST. Compute the error variance estimate s². a. C. Compute the coefficient of determination R2. Compute the value of the F statistic for the hypothesis Ho : ß1 = B2 = 0. How many degrees of freedom does this statistic have? Can the hypothesis Ho : B1 = B2 = 0 be rejected at the 5% level? Explain. d. e. f.
x 13 32 50 28 50 25 y 1 2 6 5 9 3 a.given Σx = 198, Σy = 26, Σx2 = 7602, Σy2 = 156, Σxy = 1042, and r ≈ 0.8553 b. Find x, and y. Then find the equation of the least-squares line ŷ = a + bx. (Round your answers to four decimal places.) x= y= ŷ= c. Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to four decimal places. Round your answers for the percentages to two decimal place.) r2= explained= % unexplained= % d. For a neighborhood with x = 35 hundred jobs, how many are predicted to be entry level jobs? (Round your answer to two decimal places.) hundred jobs
The U.S. national debt (in billions of dollars) for selected years from 1980 is shown in the following table. Year 1980 1985 1990 1995 2000 2004 Debt 930.2 1945.9 3233.3 4974.0 5674.2 7379.1 (a) Find the least squares regression linear function giving national debt as a function of years since 1980 (x = 0 for 1980). (Round all numerical values to two decimal places.) f(x) = (b) Use the regression line to estimate the national debt in 2005. In 2018. (Round your answers to one decimal place.) 2005 $ billion 2018 $ billion (c) Assume 310 million (0.31 billion) people in the United States in 2018. What is the estimated per capita debt? (Round your answer to the nearest thousand.) $
QUADRATIC REGRESSION 1) The following table shows the population in a certain country between the years 1880-1980 (img 1) A. Make the scatterplot and propose the approximating curve. B. Find the equation of the least squares parabola that best fits the data C. Calculate the estimated (trend) values for the data indicated in the table and compare them with the true ones. D. Using the equation, estimate the population in 1990 and 2000. E. Using the equation, estimate the population in 1860 and 1870.
The table below shows the number, in thousands, of vehicles parked in the central business district of a certain city on a typical Friday as a function of the hour of the day. Hour of the day Vehicles parked(thousands) 9 A.M. 6.2 11 A.M. 7.6 1 P.M. 7.6 3 P.M. 6.7 5 P.M. 4 (a) Use regression to find a quadratic model for the data. (Let V be the number of vehicles and t be the time in hours since midnight. Round the regression parameters to three decimal places.) V= (b) Express using functional notation the number of vehicles parked on a typical Friday at 2 P.M., and then estimate that value. (Round your answer to two decimal places.) V_____= _____ thousand

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