1. STAT 5372: Experimental Statistics
Wayne Woodward
Office: 143 Heroy
Phone: (214)
URL: faculty.smu.edu/waynew
Hours: 2:00 - 3:00 WF :00 - 4:00 Th others by appointment 1

2. Lecture 1 - 2: Review Sampling Distributions Statistical Inference
Confidence Intervals
Hypothesis Tests

3. Sampling / Sampling Distributions
Population - totality of all observations of interest
Parameters - characteristics of a population
Sample - subset of a population
random sample: observations made independently and at random

4. Examples of Statistics:
Statistic - function of random variables
- typically used to estimate parameters
Examples of Statistics:
sample mean
sample variance

5. Key Concept
Statistics are random variables and have their own distributions
- called sampling distributions

6. Sampling Distribution of the Sample Mean
IF:
Data are Normally Distributed
Observations are Independent
Then:

9. Central Limit Theorem IF: Then: Independent Observations
Sample Size is Sufficiently Large
Then:
has a an approximate Standard Normal distribution

10. Distribution of Sample Mean - s Unknown
IF:
Data Values are Normally Distributed
Observations are Independent
Then:
has a Student’s t distribution with n - 1 df

11. t-distribution -- Figure 5.16, page 229