A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The following table provides the number of cans sold per week. Use the exponential smoothing (let α=0.4 with an initial forecast for week 1 of 572) methods to forecast demand for week 13. Period 1 2 3 4 5 6 7 8 9 10 11 12 Sales 572 637 648 740 670 633 752 690 761 720 656 751 Obtain the exponential smoothing forecast. The forecast for week 13 =?is (Enter your response rounded to the nearest whole number.) Specify the mean absolute deviation (MAD) and mean absolute percent error (MAPE). (Enter your responses rounded to two decimal places.) MAD MAPE ? ?%
A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The following table provides the number of cans sold per week. Use the exponential smoothing (let α=0.4 with an initial forecast for week 1 of 572) methods to forecast demand for week 13. Period 1 2 3 4 5 6 7 8 9 10 11 12 Sales 572 637 648 740 670 633 752 690 761 720 656 751 Obtain the exponential smoothing forecast. The forecast for week 13 =?is (Enter your response rounded to the nearest whole number.) Specify the mean absolute deviation (MAD) and mean absolute percent error (MAPE). (Enter your responses rounded to two decimal places.) MAD MAPE ? ?%
A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The following table provides the number of cans sold per week. Use the exponential smoothing (let α=0.4 with an initial forecast for week 1 of 572) methods to forecast demand for week 13. Period 1 2 3 4 5 6 7 8 9 10 11 12 Sales 572 637 648 740 670 633 752 690 761 720 656 751 Obtain the exponential smoothing forecast. The forecast for week 13 =?is (Enter your response rounded to the nearest whole number.) Specify the mean absolute deviation (MAD) and mean absolute percent error (MAPE). (Enter your responses rounded to two decimal places.) MAD MAPE ? ?%
A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The following table provides the number of cans sold per week. Use the exponential smoothing (let
α=0.4
with an initial forecast for week 1 of
572)
methods to forecast demand for week
13.
Period
1
2
3
4
5
6
7
8
9
10
11
12
Sales
572
637
648
740
670
633
752
690
761
720
656
751
Obtain the exponential smoothing forecast.
The forecast for week 13 =?is (Enter your response rounded to the nearest whole number.)
Specify the mean absolute deviation (MAD) and mean absolute percent error (MAPE). (Enter your responses rounded to two decimal places.)
MAD
MAPE
?
?%
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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