# (Solved Homework): *I can't figure out numbers 1 & 3 National Scan, Inc., sells radio frequency inventory tags. Monthly sales…

*I can’t figure out numbers 1 & 3

National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:

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(Solved Homework): *I can't figure out numbers 1 & 3 National Scan, Inc., sells radio frequency inventory tags. Monthly sales…
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 Month Sales (000)Units Feb. 13 Mar. 21 Apr. 19 May. 23 Jun. 20 Jul. 26 Aug. 25

b. Forecast September sales volume using each of the following:

(1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.)

Yt              thousands

(2) A five-month moving average. (Round your answer to 2 decimal places.)

Moving average 22.6 thousands

(3) Exponential smoothing with a smoothing constant equal to .15, assuming a March forecast of 16(000). (Round your intermediate forecast values and final answer to 2 decimal places)

Forecast             thousands

(4) The naive approach.

Naive approach 25.00 thousands

(5) A weighted average using .60 for August, .15 for July, and .25 for June. (Round your answer to 2 decimal places.)

Weighted average 23.9 thousands

1)

Linear trend y = a+bx

a = intercept

b = slope

x = time period

y = forecast for demand for period x

$b = (\sum xy - n\bar{x}\bar{y})/(\sum x^{2}-n\bar{x}^{2})$

$a=\bar{y}-b\bar{x}$

n = no of peiods

$\bar{x}=\sum x/n$ = the mean of the x values

$\bar{y}=\sum y/n$ = the mean of the y values

Slope b = (635-(7*4*21))/(140-(7*4*4)) = 47/28 = 1.68

Intercept a = 21-(1.68*4) = 14.28

Y = 14.28 + 1.68x

Forecast for september(x=8) =14.28+(1.68*8) = 27.72

3)

Exponential smoothing Ft

$F_{t}=F_{t-1}+\alpha (A_{t-1}-F_{t-1})$

Ft = new forecast

Ft-1 = previous period forecast

At-1 = Previous period actual demand

$\alpha = smoothing constant$

Forecast for september = 20.27

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