STAT 5372: Experimental Statistics

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Presentation transcript:

STAT 5372: Experimental Statistics Wayne Woodward Office: 143 Heroy Phone: (214)768-2457 e-mail: waynew@smu.edu URL: faculty.smu.edu/waynew Hours: 2:00 - 3:00 WF 3:00 - 4:00 Th - others by appointment 1

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

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

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

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

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

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

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

t-distribution -- Figure 5.16, page 229