Assignment 2 is due by midnight Monday
4/29. Show your work and submit it to the Chapter 4 Assignment 2 Dropbox. This
assignment addresses forecasting your selected independent variables (Xs) using
an exponential smoothing technique. Only submit the forecast for each X
variable. Keep in mind that you need to submit X variable forecasts.. Use only
one exponential smoothing method
— the best that applies. Do not use any other forecasting techniques in this
assignment.
a) Tell me why you selected the appropriate exponential
smoothing method by commenting on data characteristics for each X variable. (you
should refer to a time series plot and autocorrelations (ACFs) for each X
variable to do this.
b) Apply the appropriate exponential smoothing forecast
technique to each X variable. Show each X variable original data, fitted values
and residuals in an excel table and show your exponential smoothing model
coefficients. (Find the best coefficient and not just use the default values.)

c) Evaluate the “Goodness To Fit” using at least two error measures — RMSE
and MAPE for each X variable fit period residuals. (Remember, Actual X – Fitted
X = X Fit Period Residuals)
d) Check the “Fit” period residual mean proximity
to zero and randomness with a time series plot; check the residual time series
plot and autocorrelations (ACFs) for trend, cycle and seasonality.
e)
Evaluate the residuals for the “Fit” period by indicating the residual
distribution using a histogram (comment on whether the distribution is normal or
not and random or not),
f) Comment on the acceptability of the model’s
ability to pick up the systematic variation in your Fit period actual data.
That is, determine the cause of the error — any Trend, Cycle or Seasonality
left in the residuals.
g) Develop a 2 year forecast for each X variable using
the best model determined above and check the forecast for reasonableness. Do
this with a time series plot of the actual data appended with your forecast for
each X variable.
Show your work and graphs in a Word document. Make
sure that you comment on statistics and graphs relevant to answering the above
questions. DO NOT leave statistics and graphs stranded. If you show something
write about it. Note that this work will become a key part of your
class presentation so do a good job on it. Submit the word document in the
assignment 6 Dropbox with your first initial, last name and Assignment 2 in the
file name.

Remember that you should do the same for each X
variable — develop a 2 year forecast for each of the X variables selected using
exponential smoothing. Keep in mind that you may need to
use different exponential smoothing models for each variable based on the trend,
cycle and seasonal characteristics of the variable data. Do not waste your
time running models that do not apply to the data. You will need them in the
two year regression forecast of the Y (Sales/Revenue) data. This will count as
extra credit.