Overview
In just three hours, discover how to create accurate forecasts
and predictions with Microsoft Excel's powerful predictive
analytics tools!
Description
Moneyballmade predictive analytics famous: now, you can put
it to work! In just three hours of expert video, Conrad Carlberg
will teach you all the core skills you need to create accurate
predictions of your own with Microsoft Excel–hands-on! Learn how to
use Excel to design and run the two most basic analyses used in
quantitative forecasting: smoothing and regression. Explore the
self-correcting nature of exponential smoothing, discover how to
use autoregression to create effective forecasts, and get
comfortable using Excel's powerful Data Analysis and Solver
add-ins. Understand trends in time series, and master differencing,
the most important technique for dealing with them. Finally, learn
about ACFs and PACFs, and uncover their patterns to identify the
best ways to forecast any given time series. These hands-on videos
are accompanied by Excel workbooks containing all sample data and
analyses: workbooks you can easily replicate and adapt for your own
needs!
About the Instructor
Conrad Carlbergis a multiple recipient of Microsoft's Most
Valuable Professional (MVP) award for Microsoft Excel. He has
written twelve books about quantitative analysis with Excel,
including
Predictive Analytics: Microsoft® Excel. As President of
Network Control Systems, Inc., he leads the development of quality
control and forecasting tools for the health industry. Carlberg
holds a Ph.D. in statistics from the University of Colorado, and
has 25 years' experience applying advanced analytical
techniques.
Skill Level
- All Levels
- Beginner
- Intermediate
- Advanced
What You Will Learn
- The essentials and basic terminology of predictive
analysis
- How to use Excel's core predictive analysis tools, including
the Data Analysis and Solver add-ins
- How to perform quantitative analyses using smoothing and
regression
- How to create effective forecasts using autoregression
- How trends in time series work, and how to handle the
challenges they create
- How to choose the best approach to forecast any time
series
Who Should Take This Course
- Every businessperson, scientist, analyst, and student who wants
to master the essentials of predictive analytics
Course Requirements
- Basic experience with Microsoft Excel
- Basic knowledge of simple statistical analysis techniques
Table of Contents
Introduction
Part 1: Moving Averages
Lesson 1: Length of Moving Averages
Lesson 2: Length's Effect on Level
Lesson 3: Weighted and Unweighted Moving Averages
Lesson 4: The Moving Average Tool and Trendlines
Part 2: Smoothing
Lesson 5: Self-Correction
Lesson 6: Smoothing Constant and Exponentiation
Lesson 7: The Exponential Smoothing Tool
Lesson 8: Detrending and Retrendng
Lesson 9: Choosing the Smoothing Constant
Part 3: Regression
Lesson 10: Simple, two-variable regression
Lesson 11: TREND() and LINEST()
Lesson 12: Problems Using Time as a Predictor
Part 4: Autoregression
Lesson 13: Simple single lag autoregression
Lesson 14: Correlograms and moving average time series
Summary
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