## Assignment #1: Exploring Demand DataChap 2: Prob 5
Chap 3: Prob 1 Chap 9.1: Tips & Suggested Steps 1-4 In this assignment you will create visualizations of time series, characterize the different patterns in the series and consider how to evaluate predictive performance. You will also get experience with Tableau/Spotfire and XLMiner.
## Assignment 2: Forecasting Sales Using SmoothingChapter 6: Problem 8
Chap 9.1: Tips & Suggested Steps 5-6 and answer the following question:- How can exponential smoothing be fitted to the series, given the inter-day and intra-day cycles? Write the type of method(s), its components and the number of seasons to use.
Download Australian Wines from ForecastingBook.com/datasets ## Assignment 3: Forecasting Traffic Using RegressionChapter 5: Problem 1Chapter 5: Problem 4
Chapter 9.1 - answer the following question:- How can a regression model be fitted to the demand series, given the inter-day and intra-day cycles? Mention the response (Y) and predictor variables (X’s) in your suggested regression model.
In this assignment, you will investigate the effect of an event on a time series by generating pre-event forecasts using linear regression. You will use linear regression to capture patterns such as trend and seasonality, and gain experience using XLMiner for generating regression-based forecasts. Download September 11 Travels from ForecastingBook.com/datasets |