In this video, the instructor illustrates making predictions with regressions.
- [Narrator] Let's talk about a specific example…using regression analysis.…In this case, we're looking at predicting…the estimated home heating oil use…by a particular customer, based on three different factors.…A variable that we call the intercept,…the temperature outside,…and the level of insulation in the customer's house.…Let's focus on these bottom three rows in the table,…and in particular, focus on the column labeled Coefficients.…These coefficients tell us the impact…on home heating oil use…in a particular month given the temperature outside…and the insulation level of the person's house.…
Now, let's see how we would use this in a prediction.…There's three steps to the prediction,…run the regression, which I showed you the output…from the previous slide,…then we're going to save those coefficients.…That was those last three rows of data.…For example, this will help us to measure the impact…for each additional inch of insulation in a person's house.…And then, finally, we're going to use those coefficients…
Join Professor Michael McDonald and discover how to use predictive analytics to forecast key performance indicators of interest, such as quarterly sales, projected cash flow, or even optimized product pricing. All you need is Microsoft Excel. Michael uses the built-in formulas, functions, and calculations to perform regression analysis, calculate confidence intervals, and stress test your results. You'll walk away from the course able to immediately begin creating forecasts for your own business needs.
LinkedIn Learning (Lynda.com) is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.
The PMI Registered Education Provider logo is a registered mark of the Project Management Institute, Inc.
- List the two methods of making decisions.
- Identify the most common method of conventional financial forecasting.
- Describe common challenges that come when trying to merge data.
- Assess the types of questions that business intelligence is best suited to answer.
- Distinguish the statistic that is most useful for estimating the impact of an X variable on a Y variable.