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.
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
- Model-driven vs. data-driven methods
- Centered and trailing Moving Average (MA)
- Exponential Smoothing (simple, double, triple)
- De-trending and seasonal adjustment
- 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
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
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This program has been a life and work game changer for me. Within 2 weeks of taking this class, I was able to produce far more than I ever had before.
The material covered in the Analytics for Data Science Certificate will be indispensable in my work. I can’t wait to take other courses. Great work!
I learned more in the past 6 weeks than I did taking a full semester of statistics in college, and 10 weeks of statistics in graduate school. Seriously.
This is the best online course I have ever taken. Very well prepared. Covers a lot of real-life problems. Good job, thank you very much!
The more courses I take at Statistics.com, the more appreciation I have for the smart approach, quality of instructors, assistants, admin and program. Well done!
This course greatly benefited me because I am interested in working in AI. It has given me solid foundational knowledge…After completing this last course, I feel I have gained valuable skills that will enhance my employability in Data Science, opening up diverse career opportunities.
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About 15 hours per week, at times of your choosing.
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.
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.
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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:
- Color Enhancer (for colorblindness)
- HelperBird (for colorblindness, dyslexia, and reading difficulties)
- Mobile Dyslexic
- Color Vision Simulation (native accessibility feature)
- Other native accessibility features instructions