п»їBA 5iphon scam Practical Organization Analysis
Group Project several: Time Series Analysis and Forecasting
Due: March 16, 2013 at the start of the class
1 . Place a time series plot. Touch upon the actual trend and seasonal habits. This is the own declaration. There is no need to operate any predicting model here.
(Insert the plot in this article. )
(Insert your comments here. )
2 . Forecasting using a Multiplicative Model:
a. Utilize the time series decomposition technique (textbook Phase 18. six; packet pp. 78-80) to deseasonalize time series and obtain seasonal crawls. Fit a linear tendency model to the deseasonalized period series. Report the installed model as well as the seasonal indices.
In season Index
1 . 154008
1 . 00262
1 . 087917
1 . 058668
1 . 118552
The fall of
1 . 039627
m. Describe the underlying trend and in season patterns based upon the multiplicative model designed in Question 2-a. Quantify the statements. For example , " There may be an way up trend. вЂќ and " Sales in December can be higher. вЂќ are not satisfactory and will bring about point deduction. " Revenue goes up by about $20, 000 every month, give or have $1, 500 for a 95% confidence. вЂќ and " Sales in December is often 16% greater than the average sales in a common year. вЂќ are what I am looking for. Does this version support the observation involved 1?
Product sales goes up by about $183, 010 every month, give or have $262 for a 95% confidenc Sales in December is generally 16% more than the average sales in a typical year;
c. Use this model and prediction sales to get January through December from the fourth season. Report the forecasts in the table below.
216. forty two
186. seventy five
3. Forecasting using an Additive Model:
a. Suit the time series data using the seasonal regression model having a linear tendency (textbook Chapter 18. a few; packet pp. 74-77). Statement the fixed model. Tip: you need to make dummy parameters.
Seasonal Regression with Geradlinig Trend
(Insert the regression output here. )
n. Describe the underlying tendency and periodic patterns based upon the additive model developed in Question 3-a. Quantify your statements (see examples I actually listed in Question 2-b). Does this model support your remark in Question 1?
(Insert the comments in this article. )
c. Use this model and prediction sales to get January through December from the fourth year. Report the forecasts in the table beneath.
Product sales Forecasts
4. If you need to choose one style and use its forecasts, which of the two designs will you select? Provide numerical evidence to support your choice.
(Insert your feedback here. )