Forecasting

Brief Description:

This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting.

Instructor(s):
Level: Intermediate

Who Should Take This Course:

Business analysts, sales forecasters, economists, financial analysts, anyone who needs to produce, interpret or assess forecasts will find this course useful. Participants should be familiar with basic statistics, including linear regression.

Dates:
March 30, 2012 to April 27, 2012September 14, 2012 to October 12, 2012
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
Register Online -$399 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise. Multiple course registrations may be entitled to tuition discounts; read more.

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Forecasting

Aim of Course:

This course will teach you how to choose an appropriate time series forecasting method, fit the model, evaluate its performance, and use it for forecasting. The course will focus on the most popular business forecasting methods: Regression models, smoothing methods including Moving Average (MA) and Exponential Smoothing, and Autoregressive (AR) models. It will also discuss enhancements such as second-layer models and ensembles, and various issues encountered in practice.

If you are already familiar with the use of these techniques and would like to know more about the theory behind the techniques then it is suggested that you may wish to consider the second course in Forecasting by Dean Wichern which goes into depth on the theory and application of the methods. See Forecasting - Advanced.

Prerequisite(s):

The equivalent of Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners).

Course Program:

SESSION 1: Characterizing time series and the forecasting goal; evaluating predictive accuracy and data partitioning

• Visualizing time series
• Time series components
• Forecasting vs. explanation
• Evaluating predictive accuracy

SESSION 2: Regression-based models

• Capturing trends with linear regression
• Capturing seasonality with linear regression
• Measuring and interpreting autocorrelation
• Evaluating predictability and the Random Walk
• Second-layer models using Autoregressive (AR) models

SESSION 3: Smoothing-based methods

• Model-driven vs. data-driven methods
• Centered and training Moving Average (MA)
• Exponential Smoothing (simple, double, triple)
• Differencing
• ARMA and ARIMA models
• Estimation of models

SESSION 4: Forecasting in practice

• Improving forecasts via ensembles
• Multiple seasonal patterns
• Automated forecasting (series partitioning, changing behavior, missing values)
• Handling managerial “forecast corrections

Organization of the Course:

This course takes place over the internet, at statistics.com for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and you will receive individual feedback on your homework answers.

Credit:
Students come to The Institute for a variety of reasons:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Program in Advanced Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).

As you begin the class, you will be asked to specify your category.

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a record of course completion will be issued by Statistics.com, upon request.

Course Text:

"Practical Time Series Forecasting" eBook is here and hardcopy is here.

Software:

Participants will need access to software that can do time series analysis. Examples and illustrations will be provided for XLMiner (an Excel add-in). The homework can all be done with XLMiner (a few exercises can be done just with Excel). (Most standard statistical software will be able to handle the majority of the procedures covered in this course.) Our teaching assistants can offer help with Minitab, XLMiner, JMP, Stata, SPSS, and SAS. For information about software that is available at no charge, or nominal charge, for statistics.com courses click here.

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Forecasting

Instructor(s):
Dates:
March 30, 2012 to April 27, 2012September 14, 2012 to October 12, 2012
Course Fee: $499
Academic Discounted Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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