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Using the model from the previous step, predict the company’s revenue for the 15th month

Using the model from the previous step, predict the company’s revenue for the 15th month

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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Step 2 of 3 : 
Using the model from the previous step, predict the company’s revenue for the 15th month. Round to four decimal places, if necessary.
 
NOTE:

Sum of X = 105
Sum of Y = 9756
Mean X =Mx = 7.5
Mean Y=My = 696.8571
Sum of squares (SSX) = 227.5
Sum of products (SP) = 8132

Regression Equation = ŷ = b0 + b1X

b1 = SP/SSX = 8132/227.5 = 35.74505

b0 = MY - b1MX = 696.86 - (35.75*7.5) = 428.76923

ŷ = 428.7692 + 35.7451X

Hence the regression equation is ;

Revenue = 428.7692  + 35.7451 (Month ) ( answer)

ANOVA df SS MS F Regression 1 290,678.786813 290,678.786813 94.34323112 Residual 12 36,972.927473 3081.077289 Total 13 327,651.714286 Coefficients Standard Error t Stat P-value Intercept 428.76923077 31.3349928 13.68339969 1.10591E-08 Month 35.74505495 3.68010827 9.71304438 4.90081E-07 Step 2 of 3: Using the model from the previous step, predict the company's revenue for the 15th month. Round to four decimal places, if necessary.
Transcribed Image Text:ANOVA df SS MS F Regression 1 290,678.786813 290,678.786813 94.34323112 Residual 12 36,972.927473 3081.077289 Total 13 327,651.714286 Coefficients Standard Error t Stat P-value Intercept 428.76923077 31.3349928 13.68339969 1.10591E-08 Month 35.74505495 3.68010827 9.71304438 4.90081E-07 Step 2 of 3: Using the model from the previous step, predict the company's revenue for the 15th month. Round to four decimal places, if necessary.
Month Revenue (Thousands of Dollars) Month Revenue (Thousands of Dollars) 1 321 8. 710 2 542 9. 799 540 10 821 4 581 11 833 641 12 850 6. 700 13 862 7 698 14 858 nmary output from a regression analysis of the data is also provided. Regression Statistics Multiple R 0.941890566 R Square 0.887157839 Adjusted R Square 0.877754326 Standard Error 55.50745256 Observations 14 ANOVA 3.
Transcribed Image Text:Month Revenue (Thousands of Dollars) Month Revenue (Thousands of Dollars) 1 321 8. 710 2 542 9. 799 540 10 821 4 581 11 833 641 12 850 6. 700 13 862 7 698 14 858 nmary output from a regression analysis of the data is also provided. Regression Statistics Multiple R 0.941890566 R Square 0.887157839 Adjusted R Square 0.877754326 Standard Error 55.50745256 Observations 14 ANOVA 3.
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