1. Forecasting MBA/510

2. Objectives Describe the use of time series analysis and forecasting in making business decisions Apply time series analysis and forecasting

3. Much like Forecasting Weather Persistence Method today equals tomorrow

4. Trends and other methods Climatology Analogue Numerical weather prediction

5. Much like forecasting … Average Absorption Time 3.6 5.8 34.6 0 10 20 30 40 Droplet size (microns) Seconds 2675761562 (Hours)

6. What we Now Expect 20 HOURS 7 HOURS 12 MIN – 4 HOURS NON-POROUS MATERIALS 8 HOURS 7 HOURS 8 MIN- 3 HOURS GRASS OR SAND 7 HOURS 50 MIN 8-50 MIN CONCRETE OR ASPHALT C 16 HOURS5 HOURS 12 MIN – 5 HOURS NON-POROUS MATERIALS 4 HOURS 25 MIN 8 MIN- 3 HOURS GRASS OR SAND 5 HOURS 25 MIN 8-50 MIN CONCRETE OR ASPHALT B 10 HOURS4 HOURS 12 MIN – 4 HOURS NON-POROUS MATERIALS 3 HOURS25 MIN 8 MIN- 3 HOURS GRASS OR SAND 4 HOURS 50 MIN 8-50 MIN CONCRETE OR ASPHALT A VAPOR HAZARD (WORST CASE) VAPOR HAZARD (BEST CASE) LIQUID HAZARD SURFACE AGENT Technical Review 40 Concrete and Asphalt 120 Painted Surfaces 55 Grass 10 Thickened Agent Recent live agent surface tests D****Test (1998 - 1999) C**** Tests (1999) N**** Test (1999)

7. What about Business forecasting?

8. Heban Lumber Mill (exercise 19.1) Plot the data on a chart. Estimate the linear trend equation by drawing a line through the data. Estimate the earnings per share for 2004. Earnings in dollars

9. Heban Lumber Mill (exercise 19.1) Sales went up $2.67 – $1.56, or $1.11 in 4 years (2001 –1997). Thus ($1.11 ÷ 4) = $0.2775 or $0.30 Y′=1.00+0.30tY′= a + btY′= 1.00 + bt

10. Heban Lumber Mill (exercise 19.1) The estimated earnings for 2004 are $3.10

11. Norton Company (Exercise 19.3) The quarterly sales for the Norton Company are given in millions of dollars for four years. Compute the quarterly seasonal index using the ratio-to-moving- average method. Full Table

12. Norton Company (Exercise 19.3) Full Table

13. Summary of MBA/510 Secondary and primary research Tools of data analysis Levels of measurement Sampling size & methods Descriptive data & Probability Normal distribution Confidence intervals Hypothesis & Testing Variables ANOVA & F-distribution Linear regression & Correlation analysis Time series analysis & Forecasting