1. FITTING TREND LINES AND FORECASTING

2.  FITTING BY EYE: inadequate technique. We will look at the following two:  3-MEDIAN METHOD AND  LEAST-SQUARES REGRESSION

3. Only works for the following original data: 1. When trend is clearly linear 2. Random 3. Secular (increasing or decreasing) Does not work on: 1. Cyclical trends 2. Seasonal trends

5. STEP 1: STATS - LIST 1: TIME - LIST 2: INDEPENDENT VARIABLE STEP 2: SET GRAPH - SETTING -TYPE: SCATTER - LIST 1: TIME - LIST 2: INDEPENDENT VARIABLE - SET STEP 3: CALC -LINEAR REG - LIST 1: TIME - LIST 2: INDEPENDENT VARIABLE - COPY FORMULA: y1 STEP 4: FORCASTING - y1 (x) -EXE

6.  The y-intercept: when time code is at 0, please be careful and consider what the data is about. Eg: Our last example, the y- intercept is the day before the opening of the salon. This has no real meaning.  The gradient (rate of change): very important. Eg: growing by approx 2 customers per day.

8.  EXERCISE 4B pg 163 Q’s 1-10