Suppose an e-commerce company wants to predict daily product sales based on average daily website visits.
Sample Data
| Avg. Daily Website Visits | Sales (Units) |
|---|---|
| 100 | 15 |
| 150 | 25 |
| 200 | 34 |
| 250 | 40 |
| 300 | 50 |
Linear Regression Model
Sales = Intercept + (Slope × Website Visits)
Assume the model calculates:
- Intercept: 2
- Slope: 0.16
So, the prediction formula (model) built is:
Sales = 2 + (0.16 × Website Visits)
Last February, there were 85 website visits to our online store. We expect an 8% increase this year in Feb.
This Feb website visits = 91.8
Feb Sales This Year = 2 + (.16 x 91.8)
Company prediction for Feb Sales This Year = 16.688 products
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