1. Experimental Design Data Normal Distribution
1st Half Review
Experimental Design
Data
Normal Distribution

2. Types of Experiments Mensurative Manipulative
Take advantage of existing variability in predictor
Manipulative
Actively change the values of the predictor

3. Treatments and Controls
Specific condition applied to all members of a group
Control
A group that does not receive the condition

4. Entities, Variables, and Values
Entity – thing or group of things we want to ask questions about
Variable – Character of entity we are going to measure
Value – result of measurement of variable
Entity
Variable
Value

5. More on Variables Ratio vs Interval vs Ordinal vs Nominal
Continuous vs Discrete
Precision vs Accuracy

6. Frequency Distribution
occurrence of the various values observed for the variable
raw frequency
counts
relative frequency
counts divided by total number of observations

7. Example from Text

8. Central Tendency Measures
Mean vs Median vs Mode

9. Measures of Dispersion
Deviation & Absolute Deviation from Mean
Sum of Squares
Variance & Standard Deviation
Coefficient of Variation

10. Normal Distribution X The Standardized Normal Curve

11. Standard Normal Deviate
68%
95%
99.7% -3 -2 -1 1 2 3

12. Example From Text

13. More than One Sample Mean of the Means Variance of the Means
Standard deviation of the mean or the Standard error of the mean

14. Example From the Text

15. Hypothesis Testing    0.95 Hypothesis about population  Not Sample
Null vs Alternate Hypothesis, One vs Two Tails
When do we reject?? 
0.95  

16. Types of Error and other Things
Type I vs Type II
Power
Significance Level
What is p???
What is α?? What is β??

17. t-Test
When do we use t-Test???

18. Critical t’s What effects critical t-value When do we reject null??
df & p
When do we reject null??
Two-Tail
if |tobserved|  tcritical; reject H0
One-Tail
???

19. Example From the Text

20. Confidence interval for t
What does it mean??
What effects it??

21. Two-Sample t-Test When do we use?? Null Hypothesis??
Standard error of the difference between the means

22. Example From Text

23. ANOVA Variance Partitions
Total = Among + Within
Grand Mean, Group Mean and associated Deviations
When do we reject based on variance ratio???

24. ANOVA When do we use?? Model I vs Model II vs Model III??
Multi-Factors??
Main Effects vs Interactions??

25. Example From Text

26. Example From Text