PSYC 331 Lecture 14 -- Probability and Sampling Distributions

PSYC 331 Lecture 14 -- Probability and Sampling Distributions

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1 PSYC 331 Lecture 14 Probability and Sampling Distributions
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2 Overview In this lecture we will learn about: Sampling distributions What are they and why do we use them? The standard error of the sample mean What is it and why do we compute it? Transforming the sample mean
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3 A Sampling Distribution Definition Walk-through an example Create the sampling distribution from the population Determine whether the sample statistics accurately approximate the population parameters (expected values) If any don’t, what is the difference (standard error) and how can we adjust to make them work?
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4 An Example – Selecting Samples from a Population Suppose we have a population of N=4, with the following values: 2, 4, 6, 8 How many distinct samples ( with replacement ) of size n=2 can we have? Hint: 2 n = 16
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Example continued What do we do? 1. Calculate the parameters of the population What parameters should we calculate? How do we do that?
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This note was uploaded on 01/15/2010 for the course PSYC 331 taught by Professor Dianealonso during the Fall '09 term at UMBC.

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PSYC 331 Lecture 14 -- Probability and Sampling Distributions

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