1. Dispersion: Range Difference between minimum and maximum values
(c) 2007 IUPUI SPEA K300 (4392)

2. Dispersion: Mean Deviation
Mean difference from the mean
Easy to understand
Difficult to handle in modeling
(c) 2007 IUPUI SPEA K300 (4392)

3. Dispersion: Variance
Average of the squares of difference from the mean
Second moment
Giving penalty for large deviations
(c) 2007 IUPUI SPEA K300 (4392)

4. Dispersion: Variance Short-cut formulae
(c) 2007 IUPUI SPEA K300 (4392)

5. Dispersion: Standard Deviation
Square root of variance
Compare to absolute deviation
(c) 2007 IUPUI SPEA K300 (4392)

6. Dispersion: 3-21on p. 124 Y Y-µ (Y-µ)^2 Y^2 10 -25 625 100 60 25 360050 15
225
2500 30 -5
900 40 5
1600 20
-15
400
210
1750
9100
Sum: 210; mean: 35 = 210/6
(c) 2007 IUPUI SPEA K300 (4392)

7. Dispersion: Computation1
N=6; µ=35, Ʃ(y-µ)^2= 1750; Ʃy^2=9100
Variance using the standard formula
(c) 2007 IUPUI SPEA K300 (4392)

8. Dispersion: Computation2
N=6; µ=35, Ʃy^2=9100
Variance using the short-cut
(c) 2007 IUPUI SPEA K300 (4392)

9. Dispersion: Computation3
N=6; Ʃy=210; µ=35, Ʃy^2=9100
Variance using the short-cut in textbook
(c) 2007 IUPUI SPEA K300 (4392)

10. Dispersion: Computation4
σ^2=291.7, s^2=350, Ʃ(y-µ)^2= 1750
Compute standard deviation
(c) 2007 IUPUI SPEA K300 (4392)