Please use attached data in CIDR excel sheet to answer below questions. I’ve add


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Please use attached data in CIDR excel sheet to answer below questions. I’ve added each tab for each part to be answered(CIDR-A,CIDR-B…)
1. The United
States Census Bureau releases monthly
and annual retail trade reports
that reflect retail economic activities in the United
States. More than thirty years of
time-series data can be downloaded at http://www.census.gov/retail/. Monthly retail sales in Food Services and
Drinking Places (in millions of
dollars), from January 1992 to December 2021, are downloaded and are available
in Exam1Data.xlsx. You are now trying to develop forecasts
for the Year 2022. For parts a and
b, do not deseasonalize the data
yet.
a. Use the single exponential smoothing1 forecasting method to forecast
the retail sales. Start your
exponential smoothing with 15,700 (millions of dollars) for January, 1992. Calculate
the mean absolute
percentage error (MAPE)
to determine the best alpha.
(You are not required to use Excel Solver, but you
may be able to find the best alpha by setting the objective to “minimize” MAPE/MAD/MSE and changing variable(s) to
the alpha value.) What is your
forecast for July (Month 7), 2022? Finally, report MAD and MSE.
b. You may have realized that some months have high demand while others have low demand. Calculate the seasonal index for
each month, deseasonalize the retail sales data, and insert a new column that shows the deseasonalized sales. Plot
the deseasonalized sales to see if there is an increasing or
decreasing trend.
c. Now suppose you consider using linear regression for your forecast. What would be good independent variable(s) for the dependent variable, retail
sales (second column)? Check out the values of Significance of F,
p-value, and adjusted R Square, and then provide their implications for your regression model. Provide MAD, MAPE, and
MSE and compare them with those you find in part a. Finally, calculate your forecast for July,
2022.
d. Find your best forecasting method and provide forecasts for the months of Year
2022 (January to December). You may want to follow “deseasonalize –
apply forecasting method – re-seasonalize”
technique and/or try a different method that takes into account of seasonality and trend in the data. Everyone will compete to find the best forecasting model although what you get in part c may turn out to be
the best. Hence, you need to report
the MAD, MAPE and MSE of your best
method for the periods from January 1992 to December 2021. Make sure
you briefly describe the method
and steps you followed.
e. When you tried causal forecasting methods such as part a, you may have realized challenges in getting an accurate forecast
during the recession of 2007-2009 and during the latest coronavirus pandemic. Discuss one or two ways to improve
your forecasts if you decide not to
use time-series forecasting methods.

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