What percent of the variation in revenue is explained by the linear time trend model

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Step 3 of 3 : 
What percent of the variation in revenue is explained by the linear time trend model? Round to two decimal places, if necessary.
 
NOTE:
 
Step 1

The regression equation for relationship between company's revenue and month is given by

Revenue = 428.7692  + 35.7451Month

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Step 2

The predicted company's revenue for 15th month can be calculated as

Revenue = 428.7692  + (35.7451 × 15) = 964.9457

So the answer is 964.9457

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.
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.
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