Forecasting Analytics

Forecasting Analytics

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

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

$589 | Enroll Now
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Overview

This course focuses on the most popular business forecasting methods: regression models, smoothing methods including Moving Average (MA) and Exponential Smoothing, and Autoregressive (AR) models. It also discusses enhancements such as second-layer models and ensembles, and various issues encountered in practice.

Intermediate Level Course
4-Week Course
100% Online Courses
ACE + CAP Credit Eligible
Expert Instructors
Teacher Assistant Support
Tution-Back Guarantee

Learning Outcomes

This class teaches students how to:

  • Visualize time series data
  • Understand the different components of time series data
  • Distinguish explanation from forecasting
  • Specify appropriate metrics to assess forecasting models
  • Use smoothing methods with time series data (moving average, exponential smoothing)
  • Adjust for seasonality
  • Use regression methods for forecasting
  • Account for autocorrelation
  • Distinguish real trend and patterns from random behavior

Who Should Take This Course

Data Scientists, data analysts, sales forecasters, marketing managers, accountants, economists, financial analysts, risk managers, anyone who needs to produce, interpret or assess forecasts will find this course useful. Participants should be familiar with basic statistics, including linear regression.

Instructors

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Dr. Galit Shmueli

Dr. Galit Shmueli

Dr. Galit Shmueli is a Distinguished Professor of the Institute of Service Science, College of Technology Management at National Tsing Hua University, Taiwan.  Previous academic appointments include the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics and Information Systems at the Indian School of Business, Hyderabad, and Associate Professor of Statistics in the Department of Decision, Operations & Information Technologies at the Smith School of Business, University of Maryland.  Dr. Shmueli's research has been published in the statistics, information systems, and marketing literature.

See Instructor Bio

Course Syllabus

Week 1

Characterizing Time Series and the Forecasting Goal; Evaluating Predictive Accuracy and Data Partitioning

  • Visualizing time series
  • Time series components
  • Forecasting vs. explanation
  • Performance evaluation
  • Naive forecasts

Week 2

Smoothing-based Methods

  • Model-driven vs. data-driven methods
  • Centered and trailing Moving Average (MA)
  • Exponential Smoothing (simple, double, triple)
  • De-trending and seasonal adjustment
  • Differencing

Week 3

Regression-based Models

  • Overview of forecasting methods
  • Capturing trend, seasonality and irregular patterns with linear regression
  • Measuring and interpreting autocorrelation
  • Evaluating predictability and the Random Walk
  • Second-layer models using Autoregressive (AR) models

Week 4

Forecasting in Practice

  • Forecasting implementation issues (automation, managerial forecast adjustments, and more)
  • Communicating forecasts to stakeholders
  • Overview of further forecasting methods (neural nets, ARIMA, and logistic regression)
  • Forecasting binary outcomes

Class Dates

2023

No classes scheduled at this time.

2024

No classes scheduled at this time.

2025

No classes scheduled at this time.

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Prerequisites

There are no prerequisites for this course.

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

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What Our Students Say​

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The TA was really helpful and very responsive to questions. Overall the course was a great experience.

Marilyn Wheatley
Minitab
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Considering all of the material that needed to be covered, I thought the course was well written and thought provoking.

Paul Anderson
Professor and Chair of Mathematics and Computer Science at Albion College
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Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.
  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.
Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

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Additional Course Information

Organization of Course

This course takes place online at The Institute 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.

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 at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software and guided data modeling problems using software.

In addition to assigned readings, this course also has an end of course data modeling project.

Course Text

“Practical Time Series Forecasting” in eBook or hardcopy, or, if you are using R, “Practical Time Series Forecasting in R.”  Those in South Asia can purchase the books online here.

Software

This is a hands-on course, and, while any software capable of doing time series forecasting can be used, assignment support is offered for two programs:

1. XLMiner, a data mining program available either (a) for Windows versions of Excel or (b) over the web. Course participants will have access to a low-cost license for XLMiner.

2. R, a free statistical programming environment.

Be sure to choose the book that corresponds to your chosen software program.

For XLMiner users:  Course participants will have receive a low-cost license for XLMiner – this is a special version, for this course. Do NOT download the free trial version of XLMiner from solver.com as it may conflict with the special course version.

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
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.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
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.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for college credit.  For recommendation details (level, and number of credits), please see this page. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.

INFORMS-CAP
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

There is no additional information for this course.

Register for This Course​

Forecasting Analytics
$589 | Enroll Now
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