The following table shows the rate R of vehicular involvement in traffic accidents (per 100,000,000 vehicle-miles) as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night onurban streets.Speed s Accident rate R20160025600302003535040600451400(a) Use regression to find a quadratic model for the data. (Round the regression parameters to two decimal places.)R =(b) Calculate R(70). (Round your answer to two decimal places.)R(70) =Explain what your answer means in practical terms.Commercial vehicles driving at night on urban streets atmiles per hour have traffic accidents at a rate ofper 100,000,000 vehicle miles.(c) At what speed is vehicular involvement in traffic accidents (for commercial vehicles driving at night on urban streets) at a minimum? (Round your answer to the nearest whole number.)mph

The dependent variable is the accident rate, R and the independent variable is speed, s. The…

Answered: The following table shows the rate R of…

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 figure shown to the right contains a scatter plot of 10 data points for trees, where the diameter of a tree at breast height (Dbh) is given in inches and the height is given in feet. The regression model is shown below, where x is the Dbh in inches and y is the height in feet. y = 0.91x +4.39 (A) Interpret the slope of the model. O A. The rate of change of height with respect to Dbh is 4.39 in/ft. O B. The rate of change of height with respect to Dbh is 0.91 ft/in. O C. The rate of change of height with respect to Dbh is 4.39 ft/in. O D. The rate of change of height with respect to Dbh is 0.91 in/ft. Height (ft) 40- 0 16 Dbh (in) 25
The annual expenditure for cell phones varies by the age of an individual. The average annual expenditure E(a) (in $) for individuals of age a (in years) is given below:a: 20, 30, 40, 50, 60, 70E(a): 502, 658, 649, 627, 476, 2131. Use quadratic regression to find the model that best represents the data.2. At what age is the yearly expenditure for cell phones the greatest? Round the answer to the nearest year. YOU MUST SHOW THE WORK FOR THIS PART!
The following table shows the rate R of vehicular involvement in traffic accidents (per 100,000,000 vehicle-miles) as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night on urban streets. Speed s Accident rate R 20 1600 25 700 30 350 35 250 40 650 45 1350 (a) Use regression to find a quadratic model for the data. (Round the regression parameters to two decimal places.) (b) Calculate R(65). (Round your answer to two decimal places.)
Data from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
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
Cheick is investigating how long his phone's battery lasts (in hours) for various brightness levels (on a scale of 0-100). His data is displayed in the table and graph below. Brightness Level (x) Hours (y) 23 6.7 27 5.9 30 7.3 36 7.2 71 3.8 72 3.6 85 3.1 94 1.9 (a) Use the Corr/Regression to find the equation for the line of best fit. Round your answers to two decimal places. ˆy = 8.74 + -0.07x (b) Interpret the slope in context. Cheick expects the battery life to go down by 0.07 hours for each increase of 1 in the brightness level. Cheick expects the brightness to decrease by 0.07 for every hour that goes by. Cheick expects his phone battery to last 0.07 hours if he keeps the brightness level at 0. Cheick expects his phone battery to last 8.74 hours if he keeps the brightness level at 0. Correct (c) What does the equation predict for the number of hours the phone will last at a brightness level of 36? 6.2 hours Round your answer to…

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