Skill Introduction

In this course we will introduce you to different methods for forecasting future events. While the topic of forecasting can be applied to many business and non-business domains, much of the discussion will focus on making financial forecasts.

We will briefly review subjective forecasting methods and evaluate the advantages and disadvantages of such approaches so that you have a better appreciation for empirical forecasting methods. We will then introduce you to time-series data, and why that type of data is useful for financial analytics.

The remainder of the course will focus on how to evaluate forecasts and forecasting models. We will conclude by introducing you to linear regression, a statistical technique for creating a linear function that can be used to make forecasts.

Learning Outcomes

Upon successful completion, you will be able to:

  • Explore subjective and data-driven forecasting methods

  • Consider how forecasts can be applied to business application

  • Evaluate the quality of a forecast

  • Evaluate the quality of a model that is used to make forecast

  • Apply regression to create explanatory forecasts in R

Course Curriculum

  • 1


    • Introduction Video: Forecasting in Practice with Jose Rodriguez

    • Introduction to the Skill

    • Glossary

  • 2

    Content and Activities

    • Subjective Forecasting

    • Business Forecasting and Time Series Data

    • Introduction to Financial Analytics

    • Knowledge Check 1

    • Distance Calculations Between Forecasts and Actual Observations

    • Metrics Used for Evaluating Financial Forecast Accuracy

    • Knowledge Check 2

    • Introduction to Forecasting -- Average Method

    • Introduction to Forecasting -- Naive Method

    • Introduction to Forecasting -- Linear Regression

    • Introduction to Forecasting -- R Example

    • Knowledge Check 3

  • 3

    Application Exercise

    • Instructions

    • Exercise Files

    • Debriefing

  • 4


    • Conclusion

    • Final Quiz

    • Survey Instructions

    • Feedback Survey

    • Survey Verification

    • Next Steps

Begin your learning today.