Ps2 for 404
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Actual historical demand for a product is:
Month (Period )
Actual
Forecast
January (1)
February (2)
March (3)
April (4)
May (5)
June (6)
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Please show all your work for each problem unless indicated otherwise.
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Where appropriate, please round each number to 2 decimal places
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Please format Excel spreadsheets for printing if you are submitting the assignment electronically.
Calculate the mean and standard deviation of actual sales.
Line number
Month (Period )
Actual
Forecast
x – Ој
(x – Ој)* (x – Ој)
January (1)
11.10
11.90
-3.43
11.79
February (2)
13.90
12.60
-0.63
March (3)
16.00
14.30
April (4)
13.70
14.90
-0.83
May (5)
14.30
17.50
-0.23
June (6)
18.20
13.70
13.44
July (7)
Total
87.20
Number of periods
Mean (Ој=Line 70/Line 90)
14.53
Sum of square deviations
28.53
What is the correlation for this data set? Hint: think about what you are correlating. The correlation between which two sets of numbers would offer meaningful information? (you do not need to show your calculations for this number)
The correlation coefficient for this data set equals 0.25. That means that there is very insignificant (almost nonexistent) correlation between the forecast values and actual data, which means that the forecasts given are only 25% accurate. In other words there is very little correlation between the actual data and the forecasts, which might also imply the inaccurate forecasting model used.
Using the NaДЇve 1 Time Series, calculate the July forecast.
According to the NaДЇve 1 Time Series technique the July forecast will equal 18.2 (the same as in June)
Using a three-month weighted moving average with the following, calculate the July forecast where:
July = t
t-1 weight = .43
t-2 weight =