Use the computer output to estimate the interceptPo and the slope B,.The regression equation is Y 797 - 4.73X.%3DPredictor CoefSE Coef TConstant 797.10186.649.20 0.000-4.7311.551 -3.05 0.006Intercept Bo:Slope B:eTextbook and MediaHintSave for LaterType here to search

The population regression equation can be written as Y = β0 + β1X, where X is the independent…

Answered: Use the computer output to estimate the…

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 data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 760 1119 1125 850 965 785 D Temperature (°F) 70.5 90.8 90.8 74.7 77.1 69.9 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy).The results of the regression were: y=ax+b a=-0.904 b=24.378 r2=0.64 r=-0.8 Use this to predict the number of sit ups a person who watches 9.5 hours of TV can do, and please round your answer to a whole number.
Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y⁢=811-3.56X. Predictor Coef SE Coef T P Constant 811.183 88.17 9.20 0.000 X -3.562 1.168 -3.05 0.006 Intercept β0: Slope β1:
Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y⁢=825-3.12X. Predictor Coef SE Coef T P Constant 825.405 89.72 9.20 0.000 X -3.119 1.023 -3.05 0.006 Intercept β0: Slope β1: Click if you would like to Show Work for this question: Open Show Work
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable, Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? 1220 1075 986 88 5 843 821 849 697 758 1170 867 939 D Chirps in 1 min Temperature ("F) What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is F (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below O A. The first variable should have been the dependent variable O B. It is unrealistically high. The value 3000 is…
Use the computer output to estimate the intercept BO and the slope B1.The regression equation is Y=795 - 3.25X Predictor Coef SE Coef T P Constant 795.449 86.46 9.20 0.000 X -3.252 1.066 -3.05 0.006 Intercept B 0:Slope B 1:
Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58.9-0.00749x, where x represents weight. Complete parts (a) through (d). Click the icon to view the car data. The site to your captio V.UVITU. D. The slope is -0.00749 and the y-intercept is 58.9. c. What is the predictor variable? ... OA. The predictor variable is highway fuel consumption, which is represented by x. OB. The predictor variable is highway fuel consumption, which is represented by y. C. The predictor variable is weight, which is represented by x. OD. The predictor variable is weight, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994 lb? The best predicted value of highway fuel consumption of a car that weighs 2994 lb is (Round to one decimal place as needed.) mi/gal.
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
Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
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
Two variables are defined, a regression equation is given, and one data point is given. Study = number of hours spent studying for an exam Grade = grade on the exam GRADE= 41.0 + 3.7 (STUDY) THE DATA POINT IS A STUDENT WHO STUDIED 10 HOURS AND RECIEVED AN 81 ON THE EXAM…
Statistics professor wants to use the number of hours (x) a student studies for a statistics final exam to predict the final exam score (y). A regression model was fit based on data collected from a class during the previous semester, with the following results: (y hat): y = 35.0 + 3X What is the slope? a. Yb. 35.0c. 3d. X

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Use the computer output to estimate the intercept Bo and the slope ß- The regression equation is Y = 797 - 4.73X. %3D Predictor Coef SE Coef T P Constant 797.101 86.64 9.20 0.000 -4.731 1.551 -3.05 0.006 Intercept Bo: i Slope B: i