QUESTION 12Suppose dfErr = 16, SST = 1917, and se = 3.9 for the simple regression ý = bo + b1(x).What is r²?O a. 0.8651O b. 0.8731OC. None of the answers is correctO d. 0.8811O e. 0.8874Click Save and Submit to save and submit. Click Save All Answers to save all answers.F1E*F2#ㅁㅁF3000000F4%MacBook ProF5F6reater than the true pF7r

Answered: Image /qna-images/answer/ac00b070-6ece-4ec3-8896-66f5b698b886.jpg

Answered: QUESTION 12 Suppose dfErr = 16,…

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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Use the following linear regression equation to answer the questions. X1 = 1.5 + 3.6x2 - 7.7x3 + 2.3x4 (a) Which variable is the response variable? O X4 O X2 O 3 Which variables are the explanatory variables? (Select all that apply.) O 3 O X4 O X1 O ×2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X, coefficient X4 coefficient (c) If x2 = 4, x3 = 9, and x4 = 10, what is the predicted value for x,? (Use 1 decimal place.) (d) Explain how each coefficient can be thought of as a "slope" under certain conditions. O If we look at all coefficients together, each one can be thought of as a "slope." O If we hold all explanatory variables as fixed constants, the intercept can be thought of as a "slope." O If we hold all other explanatory variables as fixed constants, then we can look at one coefficient as a "slope." O If we look at all coefficients together, the sum of them can be thought of as the overall…
The data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Done
Suppose the equation of the regression line for the number of emails a person recieves at a particular sales company is given by y=9+19⋅x. Where y is based on the number of accounts the person has, x. If a person has 15 accounts, find the number of emails they will recieve. Number of emails:
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Ive 249 QUESTION 24 Alles and your friend will drive Solve for x and y. Round decimals to two places. 37 For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIUS Paragraph Arial Click Save and Submit to save and submit. Click Save All Answe DELL
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=-0.667 b=26.552 r2=0.677329 r=-0.823 Use this to predict the number of situps a person who watches 12 hours of TV can do (to one decimal place)
Use the following linear regression equation to answer the questions. x1 = 1.0 + 3.9x2 – 8.4x3 + 2.4x4 Suppose x2 decreased by 4 units. What would be the expected change in x1?
Use B = -15.812961, and ₁ = 0.096300 to determine the equation of the estimated regression line. (Round your numerical answers to four decimal places.) ŷ =
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=-0.993 a=29.135 r2=0.463761 r=-0.681 Use this to predict the number of situps a person who watches 6 hours of TV can do. Round to one decimal place.
Use the following linear regression equation to answer the questions. X1 = 1.2 + 3.6x2 - 7.6x3 + 2.5x4 (a) Which variable is the response variable? O x1 O X4 O x2 O x3 Which variables are the explanatory variables? (Select all that apply.) O x1 O X4 O X3 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 6, and x4 = 4, what is the predicted value for x1? (Use 1 decimal place.) (d) Explain how each coefficient can be thought of as a "slope" under certain conditions. O If we look at all coefficients together, each one can be thought of as a "slope." If we hold all explanatory variables as fixed constants, the intercept can be thought of as a "slope." O If we look at all coefficients together, the sum of them can be thought of as the overall "slope" of the regression line. O If we hold all other explanatory variables as fixed constants, then we can look at…

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