The residual is the bit that’s left when you subtract the predicted value from the observed value. In this case, the prediction is off by 2 that difference, the 2, is called the residual. Your model isn’t always perfectly right, of course. That’s the predicted value for that day, also known as the value for “Revenue” the regression equation would have predicted based on the “Temperature.” So if we insert 30.7 at our value for “Temperature”…
That 50 is your observed or actual output, the value that actually happened. Let’s say one day at the lemonade stand it was 30.7 degrees and “Revenue” was $50. The regression equation describing the relationship between “Temperature” and “Revenue” is: Calculating a Group’s Contribution to Overall Scores (Studio).Displaying Total Volume on Widgets (Studio).Percent Total & Percent Parent (Studio).Adding Reference Lines to Widgets (Studio).
