Part One: Time Series
?
?
?
Perform time series analysis on the total dollar amount of residential real estate
sales on your neighborhood.
Use sales beginning in the year 2009 to develop your model. Develop a
forecast for the next 8 quarters of sales.
Present your findings to include all the below:
1. A table that shows the forecast numbers, confidence bands for the next 8
quarters.
Define the model type that you used (Additive or Multiplicative) and why
you used it.
Seasonal changes look about the same over time, so additive
decomposition is best.
3. Determine whether your model factored trend and seasonality and why it
did or did not.
In the time series, the data keeps repeating short cycles, so my model
is seasonal
Part Two: Regression Forecast
In this part, you are to develop two models. One that includes time only as a predictor.
The other includes both time and seasonality. For both models, list and discuss the
below points.
1. The model equation.
2.
Total sales=(5.932e+05 )*Time (4.749e+09)+Quarter(Q2= 2.689e+06, Q3=
3.041e+06, Q4= 1.770e+07)
Total sales=(6.228e+05) * Time (4.983e+09)
2. The significance of each predictor. What does that value represent and what
does it mean for your model?
For the first equation, we have p=0.01083
Purchase answer to see full
attachment