1. Trend Fitting in Excel
Copyright (c) 2008 by The McGraw-Hill Companies. This material is intended solely for educational use by licensed users of LearningStats. It may not be copied or resold for profit.

2. Step 1: Data Entry Step 1. Enter the data.
Sales of EDS corporation in billions of dollars.
Goal is to project the trend for the next three years.
Source Detroit Free Press, May 2, 2002, p. 2C

3. Step 2: Graph Type
Step 2. Use the Chart Wizard to make a line or bar graph.

4. Step 3: Time Axis Labels
Step 3. Insert X-axis labels (years).

5. Step 4: Add Titles
Step 4. Add title and axis units.

6. Step 5: Embellishments
Before
Step 5. Improve the chart (fonts, colors, axis scales).
After

7. Step 6: Fitted Trend
Step 6. Right-click the data and choose Add Trendline.

8. Step 7: Trend and Options
Step 7. Select the trend model. Click Options to display the equation and R2 and choose the number of forecasts.

9. Step 8: Fine-Tuning
Step 8. You can right-click the trend line to change its color. Drag the fitted equation to where it looks good.
Before
After

10. Step 9: Add Labels
Step 9. To label the X-axis with the forecast years, right click the graph, choose Source Data, and reset the X-axis labels to include
Final Graph

11. Step 10: Numerical Forecasts
Step 10. If you want numerical forecasts, you must create a time index column (1, 2, 3, ... ) and enter the fitted trend formula in each forecast cell.
Note that the formula y = x must be modified for correct cell formula syntax.
=1.4114*B
=1.4114*B
=1.4114*B

12. Changing the Trend Type
Right-click the trend line, choose Format Trendline, and select the trend you want. Excel offers 6 trend models.

13. Choosing a Trend Type Considerations
Occam's Razor says we should choose the simplest model that fits the data.
Avoid higher order polynomials (they produce bizarre forecasts).
Unfamiliar trend models may be hard to explain to other people.

14. Bottom Line Linear trend is most familiar. But data may be nonlinear.
Exponential trend is good for:
long-term financial data
rapidly-growing data (must be > 0)
Other trends are less common.
Judgment forecasts are also used.