The monthly sales for Yazici Batteries, Inc., were as follows: Month Jan Feb Mar

Question

The monthly sales for Yazici Batteries, Inc., were as follows:

  

Month

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Sales

2121

2323

1717

1414

1111

1515

1515

1818

2222

2222

2020

2222

This exercise contains only parts b and c.

b) The forecast for the next month (Jan) using the naive method =

2222

sales (round your response to a whole number).

The forecast for the next period (Jan) using a 3-month moving average approach =

21.3321.33

sales (round your response to two decimal places).

The forecast for the next period (Jan) using a 6-month weighted average with weights of

0.100.10,

0.100.10,

0.100.10,

0.200.20,

0.200.20,

and

0.300.30,

where the heaviest weights are applied to the most recent month =

20.520.5

sales (round your response to one decimal place).

Using exponential smoothing with

alpha

=

0.300.30

and a September forecast of

18.0018.00,

the forecast for the next period (Jan) =

20.7920.79

sales (round your response to two decimal places).

Using a method of trend projection, the forecast for the next month (Jan) =

nothing

sales (round your response to two decimal places).

Just need help and work shown on the trend projection to see what im doing wrong. thanks

Month

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Sales

2121

2323

1717

1414

1111

1515

1515

1818

2222

2222

2020

2222

Explanation / Answer

Solution:

The regression equation is 1668.03 + 28.25175X

When X = 13 (Next month January), the sales would be

Y = 1668.03 + 28.25175 (13)

Y = 2035.30

SUMMARY OUTPUT Regression Statistics Multiple R 0.257559 R Square 0.066337 Adjusted R Square -0.02703 Standard Error 400.8031 Observations 12 ANOVA df SS MS F Significance F Regression 1 114137.1 114137.1 0.710501 0.418982 Residual 10 1606432 160643.2 Total 11 1720569 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 1668.03 246.6773 6.761994 4.97E-05 1118.399 2217.662 X Variable 1 28.25175 33.51684 0.842912 0.418982 -46.4284 102.9319

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