The exponential smoothing model from part b, with α=0.1, yields a mean squared error of 14.3...
The exponential smoothing model from part b, with α=0.1, yields a mean squared error of 14.3 for this time series. If we set α equal to 0.05, the mean squared error is 15.9. If we set α equal to 0.3, the mean squared error is 10.5. Which of these three values of α (0.05, 0.1, 0.3) would be the most appropriate for predicting future weekly sales?
Homework Answers
SOLUTION:-
The answer is 0.3.
Because,
- The littler the estimation of MSE is the best the model is.
- From the given data 0.3 is having the least MSE is 10.5.
- Finally 0.3 would be the most suitable for anticipating future week after week deals.
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The exponential smoothing model from part b, with α=0.1, yields
a mean squared error of 14.3...
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The following ANOVA model is for a multiple regression model with two independent variables: Degrees of Sum of Mean Source Freedom Squares ...
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Degrees
of
Sum
of
Mean
Source
Freedom
Squares
Squares
F
Regression
2
60
Error
18
120
Total
20
180
Determine the Regression Mean Square (MSR):
Determine the Mean Square Error (MSE):
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Property Market_Val Sale_Price
1 181.44 382.0
2 191.00 230.0
3 159.83 220.0
4 189.22 277.0
5 151.61 205.0
6 166.40 250.0
7 157.09 235.0
8 211.74 284.0
9 146.45 247.7
10 131.80 159.0
11 131.05 200.0
12 191.98 285.0
13 138.85 170.0
14 147.95 215.0
15 121.98 149.0
16 113.08 165.0
17 138.02 205.0
18 162.65 262.5
19 ...
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The following ANOVA model is for a multiple regression model
with two independent variables:
Degrees
of
Sum
of
Mean
Source
Freedom
Squares
Squares
F
Regression
2
60
Error
18
120
Total
20
180
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Determine the Mean Square Error (MSE):
Compute the overall Fstat test statistic.
Is the Fstat significant at the 0.05 level?
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income. The Regression Sum of Squares (SSR) was 360 and...
Please answer the whole question, I need them all
I will give thumbs up
This is should be the
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Property Market_Val Sale_Price
1 181.44 382.0
2 191.00 230.0
3 159.83 220.0
4 189.22 277.0
5 151.61 205.0
6 166.40 250.0
7 157.09 235.0
8 211.74 284.0
9 146.45 247.7
10 131.80 159.0
11 131.05 200.0
12 191.98 285.0
13 138.85 170.0
14 147.95 215.0
15 121.98 149.0
16 113.08 165.0
17 138.02 205.0
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