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use the photos answer question: -interpret the regression statistics -explain whether the model is significant - what is the coefficients of the model - do the variables used in the model make sense why or why not - identify other variables that may improve the model Denton Hospitality Inc. has hired your consulting firm to evaluate and manage cashflows. Specifically, you have been asked to build a valid and reliable model to predict total expenses so management can better manage cashflows. You and your team prepared the following regression Hospitality Inc - Total Expenses Prediction Model SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Regression Statistics Total 0810435721 0656806059 062160668 7944854158 Intercept Number of rooms Hours Worked, Front Desk Hours Worked, GM Hours Worked, Housekeeping 44 of 4 39 43 (131.136.43) 2,670.21 29.3 SS Coefficients Standard Error Stat 52.01 13.41 MS 471E+11 118E-11 1865959 246E+11 6.31E-09 7:17E+11 F Significance F 1.21E-08 P-value 1210719 -108313 0.285403 587.7595 4.543032 5.23E-05 9.270823 3.160299 0.003044 18.93043 2747581 0.009043 4.683324 2862522 0.006728

use the photos answer question: -interpret the regression statistics -explain whether the model is significant - what is the coefficients of the model - do the variables used in the model make sense why or why not - identify other variables that may improve the model Denton Hospitality Inc. has hired your consulting firm to evaluate and manage cashflows. Specifically, you have been asked to build a valid and reliable model to predict total expenses so management can better manage cashflows. You and your team prepared the following regression Hospitality Inc - Total Expenses Prediction Model SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Regression Statistics Total 0810435721 0656806059 062160668 7944854158 Intercept Number of rooms Hours Worked, Front Desk Hours Worked, GM Hours Worked, Housekeeping 44 of 4 39 43 (131.136.43) 2,670.21 29.3 SS Coefficients Standard Error Stat 52.01 13.41 MS 471E+11 118E-11 1865959 246E+11 6.31E-09 7:17E+11 F Significance F 1.21E-08 P-value 1210719 -108313 0.285403 587.7595 4.543032 5.23E-05 9.270823 3.160299 0.003044 18.93043 2747581 0.009043 4.683324 2862522 0.006728

MATLAB: An Introduction with Applications
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 photos to answer the question: -interpret the regression statistics -explain whether the model is significant - what is the coefficients of the model - do the variables used in the model make sense why or why not - identify other variables that may improve the model Denton Hospitality Inc. has hired your consulting firm to evaluate and manage cashflows. Specifically, you have been asked to build a valid and reliable model to predict total expenses so management can better manage cashflows. You and your team prepared the following regression. Hospitality Inc - Total Expenses Prediction Model SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Regression Statistics Total 0810435721 0.656806059 062160668 7944854158 Intercept Number of rooms Hours Worked, Front Desk Hours Worked, GM Hours Worked, Housekeeping 44 df 4 39 43 SS MS 7.17E+11 4.71E+11 118E+11 18.65959 2.46E+11 6.31E+09 F Significance F Coefficients Standard Error Stat (131.136.43) 2,670.21 1.21E-08 P-value 1210719 -1.08313 0.285403 587.7595 4.543032 5.23E-05 29.3 9.270823 3.160299 0.003044 52.01 18.93043 2747581 0.009043 1341 4.683324 2.862522 0.006728
Transcribed Image Text:use the photos to answer the question: -interpret the regression statistics -explain whether the model is significant - what is the coefficients of the model - do the variables used in the model make sense why or why not - identify other variables that may improve the model Denton Hospitality Inc. has hired your consulting firm to evaluate and manage cashflows. Specifically, you have been asked to build a valid and reliable model to predict total expenses so management can better manage cashflows. You and your team prepared the following regression. Hospitality Inc - Total Expenses Prediction Model SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Regression Statistics Total 0810435721 0.656806059 062160668 7944854158 Intercept Number of rooms Hours Worked, Front Desk Hours Worked, GM Hours Worked, Housekeeping 44 df 4 39 43 SS MS 7.17E+11 4.71E+11 118E+11 18.65959 2.46E+11 6.31E+09 F Significance F Coefficients Standard Error Stat (131.136.43) 2,670.21 1.21E-08 P-value 1210719 -1.08313 0.285403 587.7595 4.543032 5.23E-05 29.3 9.270823 3.160299 0.003044 52.01 18.93043 2747581 0.009043 1341 4.683324 2.862522 0.006728
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