Using simple exponential smoothing and the following time series data, respond to each of the items. Period Demand 1 72 2 60 3 27 4 52 5 26 6 46 7 52 8 28 9 53 10 50 11 57 12 87 13 22 14 56
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Using simple exponential smoothing and the following time series data, respond to each of the items.
Period | Demand |
1 | 72 |
2 | 60 |
3 | 27 |
4 | 52 |
5 | 26 |
6 | 46 |
7 | 52 |
8 | 28 |
9 | 53 |
10 | 50 |
11 | 57 |
12 | 87 |
13 | 22 |
14 | 56 |
I need help! Please explain, thanks.
![b. Compute all possible forecasts using a smoothing coefficient (a) of 0.4. (Negative amounts should be indicated by a minus sign.
Round your answers to 2 decimal places.)
Exponential
Smooth
Absolute Error
Period
Demand
Error
1
72
0.00
0.00
2
60
72.00
(12.00)
27
67.20
4
52
26
46
7
52
8
28
46.70
53
10
50
11
57
12
87
50.90
13
22
14
56
15
c. Compute all possible forecasts using a smoothing coefficient (a) of 0.9. (Negative amounts should be indicated by a minus sign.
Round your answers to 2 decimal places.)
Exponential
Smooth
Period
Demand
Error
Absolute Error
1
72
60
3
27
4
52
26
6
46
7
52
28
53
10
50
11
57
12
87
13
22
14
56
15](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5541ef45-4397-4265-b662-29882e411e63%2Fbe65939e-5e1b-49c2-b2f6-c6014bfe22bf%2F5avwyke_processed.png&w=3840&q=75)
![d. Compute the MADS for each exponential smoothing forecast. (Round your answers to 2 decimal places.)
Average Forecast
For an alpha of 0.4, the MAD
For an alpha of 0.9, the MAD
e. Which forecast model would you choose? Why?
The forecast using the smoothing coefficient (a) of
model is to be chosen because it has a
measure of error (MAD).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5541ef45-4397-4265-b662-29882e411e63%2Fbe65939e-5e1b-49c2-b2f6-c6014bfe22bf%2Fkahaihd_processed.png&w=3840&q=75)
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