-tabos lockQuestion 1 of 8ACurrent Attempt in ProgressTwo variables are defined, a regression equation is given, and one data point is given.escHgtheight in inchesAgeage in years of a childHgt = 24.5+2.79(Age)=The data point is a child 12 years old who is 60 inches tall.<* Your answer is incorrect.(a) Find the predicted value for the data point and compute the residual.Enter the exact answers.Predicted value= i 57.28Residual i 2.781https://education.wiley.com/was/ui/v2/assessment-player/index.html?launchid=9e9e9f24-d616-46e6-8564-28124a1dda04#QA1N2WS#Q3XHoption commandinchesEinchesD$4RFL%стото5TVMacBook Pro6GY&7BH82/3 E|||N(9*KM

The question is about regression.Given :Regression equation :To find :a ) Predicted value for given…

Answered: Two variables are defined, a regression…

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 3000chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1004 952 1237 1116 1177 1249 Temperature (°F) 83.1 76 95.1 87.5 92.1 88.4 What is the regression equation? (^ over y)=_____+_____x (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 3000chirps 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. A. It is…
The multiple regression describes how the mean value of y is related to the xi independent variables. The parameters ?i are used to describe how the mean value of y changes for a one-unit increase in xi when the other variables are held constant. The given estimated regression equation follows where x1 is the high-school grade point average, x2 is the SAT mathematics score, and y is the final college grade point average. ŷ = −1.38 + 0.0232x1 + 0.00482x2 If the variable x2 is held constant, then only changes in x1 will impact the predicted values of ŷ. Since the coefficient of x1 is positive, for each one-unit increase of x1, the values of ŷ will increase by the value of ?1, where ?1 = . In context, for each one point increase of the high-school grade point average, the final college grade point average will increase by this amount when the SAT mathematics score does not change. If the variable x1 is held constant, then only changes in x2 will impact the predicted values of ŷ. Since the…
The data show The chest size and weight of several bears find regression equation, letting chest size be the independent variable then find the best predicted weight of a bear with a chest size of 51 inches is the result close to the actual weight of 422 pounds use a significance level of 0.05 Chest size : 45, 50, 43, 43, 52, 52. Weight : 352, 374, 275, 314, 440, 367.
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=ax+b a=-0.889 b=31.442 r²=0.3721 r=-0.61 Use this to predict the number of situps a person who watches 4 hours of TV can do (to one decimal place)
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 924 1150 840 1166 1087 930 Temperature (°F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be…
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 1118 796 1161 918 1103 1219 Temperature (F) 82 72.2 92.2 73 87.5 94.4
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…
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? E Click the icon to view the table of regression equations. Choose the correct answer below. O A. The equation CITY = 6.65 - 0.00161WT + 0.675HWY is best because it has a low P-value and the highest adjusted value of R2. O B. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it has a low P-value and the highest value of R?. OC. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it uses all of the available predictor variables. O D. The equation CITY = - 3.14 + 0.823HWY is best because it has a low P-value and its R2 and adjusted R? values are comparable to…
Using the data in the Excel spreadsheet "auto.xlsx", estimate a regression to answer the following question. A 1 inch increase in LENGTH corresponds to a _________________ increase in MPG (miles per gallon). Use negative values if it results in a decreased price. Round your answers to two decimals. make price mpg rep78 headroom trunk weight length turn displacement gear_ratio foreign AMC Concord 4,099 22 3 3 11 2,930 186 40 121 3.58 Domestic AMC Pacer 4,749 17 3 3 11 3,350 173 40 258 2.53 Domestic AMC Spirit 3,799 22 3 12 2,640 168 35 121 3.08 Domestic Buick Century 4,816 20 3 5 16 3,250 196 40 196 2.93 Domestic Buick Electra 7,827 15 4 4 20 4,080 222 43 350 2.41 Domestic Buick LeSabre 5,788 18 3 4 21 3,670 218 43 231 2.73 Domestic Buick Opel 4,453 26 3 10 2,230 170 34 304 2.87 Domestic Buick Regal 5,189 20 3 2 16 3,280 200 42 196 2.93 Domestic Buick Riviera 10,372 16 3 4 17 3,880 207 43 231 2.93 Domestic Buick Skylark 4,082 19 3 4 13 3,400 200 42 231…
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.
Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|

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