An automotive engineer computed a least-squares regression line for predicting the gas mileage (y) in miles per gallon of a certain vehicle from its speed (x) in miles per hour. The result is y= -0.14x+38.78. Predict the gas mileage when the vehicle is travelling at 55 miles per hour. Round your answer to one decimal place. Only write a number as your answer.

An automotive engineer computed a least-squares regression line for predicting the gas mileage (y) in miles per gallon of a certain vehicle from its speed (x) in miles per hour. The result is y= -0.14x+38.78. Predict the gas mileage when the vehicle is travelling at 55 miles per hour. Round your answer to one decimal place. Only write a number as your answer.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

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=a+bx b=-0.66 a=25.376 r²=0.390625 r=-0.625 Use this to predict the number of situps a person who watches 2.5 hours of TV can do. place. Round to one decimal
There is a linear relationship between the number of chirps made by the stiped ground cricket and the air temperature. It was determined that the linear regression model is: y = 25.2 + 3.3x where x is the number of chirps per minute and y is the estimated temperature in degrees Fahrenheit. What is the predicted number of chirps made when the temperature is 60 degrees Fahrenheit? Round to the nearest integer. Do not include units.
A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has found a linear regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. What is the predicted temperature for 90 chirps per minute? 18.9 degrees 227.6 degrees 23.3 degrees 61.1 degrees
A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best graphic to use to evaluate the appropriateness of the model?
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.493x - 83.403. Complete parts (a) and (b) below. A Average Weekly Wages (state), x Average Weekly Wages (federal), y 764 1003 766 1048 791 1119 (a) Find the coefficient of determination and interpret the result. r² = 0 (Round to three decimal places as needed.) 800 1152 843 1201 887 1250 924 1277 939 1306
A biologist collected data on a sample of 20 porcupines. She wants to be able to predict the body mass of a porcupine (M, in grams) based on the length of the porcupine (L, in cm). Her least squares regression equation is M = – 3089 + 175.6L. Predict the body mass of a porcupine that is 51 cm long. Report your answer using one decimal place. O 5661.0 g O 5732.5 g O 5866.6 g O 6139.2 g eTextbook and Media Save for Later Last saved 3 minutes ago. Attempts: 2 of 3 used Submit Answer Saved work will be auto-submitted on the due date. Auto- submission can take up to 10 minutes.
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
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.7 per 10 million people? X Click the icon to view the data. Find the equation of the regression line. ŷ=+x (Round the constant to one decimal place as needed. Round the coefficient to thre Data table Internet Users Per 100 80.1 79.2 78.4 45 82.9 38.4 89.5 88.8 79.1 83.3 52.7 76.5 57.1 79.4 93.1 94.8 64.5 57.7 67.3 94.1 84.6 86.6 78.5 Nobel Laureates 5.5 24.4 8.7 0.1 6.1 0.1 25.4 7.6 9 12.8 1.9 12.6 3.3 1.5 11.3 25.5 3.1 1.9 1.7 32 31.3 18.8 10.8
Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20minutes. How does the result compare to the actual tip amount of $4.55? Distance 1.40 1.65 0.68 1.32 8.51 1.80 1.02 12.71 Time 18.00 11.00 6.00 8.00 31.00 25.00 8.00 27.00 Fare 12.30 9.80 6.30 7.80 31.75 16.30 7.80 36.80 Tip 2.46 1.96 1.89 0.00 2.98 1.50 2.34 0.00 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.) The best predicted tip for a ride that takes 20 minutes is $enter your response here. (Round to the…
A regression was run to determine if there is a relationship between hours of TV watched per day, xx, and number of sit-ups, yy, a person can do in a minute.The results of the regression were: y=ax+b a=-1.399 b=26.311Use this to predict the number of sit-ups a person who watches 12.512.5 hours of TV can do in a minute. Round to the nearest whole number.