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 dayVehicles parked(thousands)6.1Hour of the day9 A.M.11 A.M7.61 P.M.3 Р.М.5 P.M.7.66.53.8(a) Use regression to find a quadratic model for the data. (Let V be the number of vehicles and t be the timehours 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.)thousand

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Answered: The table below shows the number, 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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Tuition($) Applicant Pool Applicant 950 76210 11040 1225 78000 10940 1325 67420 8670 1350 70380 9040 1500 62580 7410 1675 59260 7080 1800 57930 6350 1975 60130 6110 a. Using POMQM, develop the multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Determine the forecast for freshman applicants for a tuition rate of $1700 per semester, with a pool of applicants of 63000.
Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 2 104.004228 8.49446952 MS 522.303829 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared Root MSE = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What is the predicted height for a child born to a mother…
pediatrician wants to determine the relation that exists between a child's height, x, and head circur nd head circumferences and obtains the accompanying data. Complete parts (a) through (e). Data Table A Click the icon to view the data table. Round to four decimal places as needed.) Full data set B Нead Head (b) Use the regression equation to predict the head circumference of a child who is 25 inches tall. Height, x circumference, Height, x circumference, (inches) (inches) y (inches) y (inches) The predicted value of the head circumference of a child who is 25 inches tall is 17.05 inches. (Round to two decimal places as needed.) 27.75 17.7 26.5 17.3 24.5 17.1 27 175 25.5 17.1 26.75 17.3 (c) Compute the residual based on the observed head circumference of the 25-inch-tall child in the t 26 26.75 17.5 17.3 25 16.9 27.5 17.5 The residual based on the observed head circumference of the 25-inch-tall child is inches. 27.75 17.6 (Round to two decimal places as needed.) Print Done Enter your…
Use the data shown in the graph to write a quadratic regression equation. Then predict the box office revenue in 2013. Let x represent the number of years since 2000. Millions of dollars 32- 189 31+ 30- Box office revenue 28.9 29.4 28.7 30.8 29- 28- 27- 2004 2005 2006 2007 2008 2009 Year
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
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
The computer output below shows the result of a linear regression analysis for predicting the concentration of zinc, in parts per million (ppm), from the concentration of lead, in ppm, found in fish from a certain river. Which of the following statements is a correct interpretation of the value 19.0 in the output? On average there is a predicted increase of 19.0 ppm in concentration of lead for every increase of 1 ppm in concentration of zinc found in the fish. On average there is a predicted increase of 19.0 ppm in concentration of zinc for every increase of 1 ppm in concentration of lead found in the fish. The predicted concentration of zinc is 19.0 ppm in fish with no concentration of lead. The predicted concentration of lead is 19.0 ppm in fish with no concentration of zinc. Approximately 19% of the variability in zinc concentration is predicted by its linear relationship with lead concentration.
An ice cream truck owner collects data on the number of sales made each day and the average temperature that day. He computes a regression line for predicting the number of sales based on how far the daily temperature is from freezing (0 degrees Celsius) and finds sales = 3.22 - 1.8 (degrees over 0 Celsius). Identify the "y-intercept". A. -1.8 B. 1.8 C. 3.22 D. 0
The cost of a flight is related to the distance traveled: Miles Cost ($) 225 38.5 525 76.1 1,100 119 1,375 142 1,950 200 2,250 244 a)Graph the scatter plot on your calculator. Is the data linear, quadratic, or exponential? b) Use the appropriate regression to find the equation of best fit. c) Use your model to predict the cost of a flight that travels 800 miles? Is this interpolation or extrapolation? d) Use your model to predict the cost of a flight that travels 3000 miles. Is this interpolation or extrapolation?

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