Historical demand for a product is as follows: 
DEMAND  
April  58 
May  54 
June  74 
July  58 
August  76 
September  73 
a. 
Using a simple fourmonth moving average, calculate a forecast for October. (Round your answer to 2 decimal places.) 
Forecast for October 
b. 
Using single exponential smoothing with ? = 0.10 and a September forecast = 61, calculate a forecast for October. (Round your answer to 2 decimal places.) 
Forecast for October 
c. 
Using simple linear regression, calculate the trend line for the historical data. Say the X axis is April = 1, May = 2, and so on, while the Y axis is demand. (Round your intercept value to the nearest whole number and slope value to 2 decimal places.) 
Y = + t 
d. 
Calculate a forecast for October using your regression formula. (Round your answer to 2 decimal places.) 
Forecast for October 

a)
Four period moving average is the average of previous 4 period actual data
Forecast for October = (73+76+58+74)/3 = 281/4 = 70.25
Forecast for October = 70.25
b)
Exponential smoothing F_{t}
F_{t} = new forecast
F_{t1} = previous period forecast
A_{t1} = Previous period actual demand
Forecast fot October = 61+0.1*(7361) = 62.2
Forecast fot October = 62.2
c)
Linear trend y = a+bx
a = intercept
b = slope
x = time period
y = forecast for demand for period x
n = no of peiods
= the mean of the x values
= the mean of the y values
Slope b = (1438(6*65.5*3.5))/(91(6*3.5*3.5)) = 62.5/17.5 = 3.57
Intercept a = 65.5  (3.57*3.5) = 53
Y = 53 + 3.57x or Y = 53+3.57t
d) Forecast for October (x= 7) Y = 53+3.57*7 = 77.99
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