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Psy 202- Chapter 5

by: T'Keyah Jones

Psy 202- Chapter 5 Psy 202

T'Keyah Jones
GPA 3.0

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About this Document

These notes cover the chapter 5 topic of Sampling and Confidence Intervals
Elementary Statistics
Dr. Melinda Redding
Class Notes
Statistics, Psychology
25 ?




Popular in Elementary Statistics

Popular in Psychology (PSYC)

This 2 page Class Notes was uploaded by T'Keyah Jones on Monday September 19, 2016. The Class Notes belongs to Psy 202 at University of Mississippi taught by Dr. Melinda Redding in Fall 2016. Since its upload, it has received 5 views. For similar materials see Elementary Statistics in Psychology (PSYC) at University of Mississippi.


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Date Created: 09/19/16
September 20, 2016 Elementary statistics a) Random Sample All cases in the population have an equal chance of being selected Statistical test are built around random sample Does not guarantee representative sample Sampling error Reflects discrepancies between sample values and population values due to random factors Random chance b) Sampling Distribution Get from various types of samples Creating distribution from statistics Calculating all samples Standard deviation of this distribution is called standard error of the means (M) c) Central Limit Theorem Core of inferential statistics The mean of the samples will create a normal distribution Mean of sampling distribution = mean of population All samples have to be the same size When  is unknown, the standard deviation of sample can be used to estimate the standard error of the mean: S = _S_ M √N d) 95% Confidence Intervals Range of scores built around a sample value, such as a mean, M, that is assumed to contain the population mean, μ. Formula: M ± 1.96 ( M Example N= 81 M= __ = 12 = 1.33  M 1.33 = 12 √N √81 M=100 95% C. I. = M ±1.96 (M) =100 ± 1.96(1.33) =100 ± 2.6068 = Ranges from 97.39 to 102.61


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