1. South Dakota School of Mines & Technology Data Analysis Industrial Engineering

2. Data Analysis Empirical Distributions Industrial Engineering

3. Empirical Cumulative n i x F ) ( - =
Rank Order the data smallest to largest
Example: Suppose we collect gpa’s on 10 students
3.5, 2.8, 2.7, 3.3, 3.0, 3.9, 2.9, 3.0, 2.4, 3.1 n i x F
0.5 ) ( - =

4. Empirical Cumulative n i x F 0.5 ) ( - = Rank Obs 1 2.4 0.05

5. Empirical Cumulative x F ) ( Obs 2.4 0.05 2.7 0.15 2.8 0.25 2.9 0.35
Obs

6. Time to Failure

7. Exponential Distributionf x e ( )   
Density
Cumulative
Mean /
Variance /2 F 1
, x > 0

8. Inventory Data

9. Diameter Errors

10. Normal Distribution

11. Scatter Plots (Paired Data)
Shows the relationship between paired data
Example: Suppose for example we wish to look at state per student expenditures versus achievement results on the Stanford Achievement Test

12. Scatter Plots (Paired Data)