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Chapter 2

by: Upasana Raja

Chapter 2 PSY 1003

Upasana Raja
Statistics for Psychology
Jennifer Pacyon

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Statistics for Psychology
Jennifer Pacyon
75 ?




Popular in Statistics for Psychology

Popular in Psychlogy

This 3 page Bundle was uploaded by Upasana Raja on Wednesday September 23, 2015. The Bundle belongs to PSY 1003 at Temple University taught by Jennifer Pacyon in Summer 2015. Since its upload, it has received 76 views. For similar materials see Statistics for Psychology in Psychlogy at Temple University.


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Date Created: 09/23/15
Chapter 2 Measure of Central Tendencv Mean Means the average score This is most commonly used statistic which provides a simple single number that gives a rough summary of the distribution Does not tell you how spread out the scores are variance Does not tell you how many scores are close to the mean Median Means the value that lies in the middle after ranking all the scores Median marks the 50th percentile This measurement is useful when scores are skewed or when there are outliers extreme scores Mode Means the most frequently occurring score This is the least used measure because it provides the least amount of information of a given data Negatively Skewed When most of the scores are clustered near the higher end of the distribution tail is in the negative end Positively Skewed When most of the scores are clustered near the lower end of the distribution tail is in the positive end Measures of Variability 1 Range It compares the minimum score with the maximum score Range Max value Min value It is a crude indication of the spread of the scores because it does not tell us much about the shape of the distribution and how much the scores vary from the mean 2 lnterquartile range The IQR is the difference between the largest and smallest score that marks the 75th percentile 3rCI quartile and the 25th percentile 1St quartile This helps negate problems outliers cause and gives a better representation of the scores 3 Variance Provides the statistical average of the amount of dispersion in a distribution of scores Basically gives you an average of how variable the scores are 4 Standard Deviation The average deviation between individual scores in a distribution and the mean score Provides a useful measure of how spread out the scores are in a distribution When combined together the mean and standard deviation provide a good picture of what the distribution of scores actually look like Calculating the Variance and SD Hl E I l l l DIM Ir T M 1M FE 1 Sample Population Why is the denominator for a sample n1 The sample if an overestimation of the population nl helps to reduce the overestimation nl particularly effects smaller sample sizes but does not necessarily effect larger sample sizes because larger sample sizes are more representative of the population Steps for Calculating the Variance and SD Step 1 List your sample data in a column Step 2 Obtain the Average of your sample data Step 3 Subtract each sample data point from the mean Step 4 Square the results of each sum should equal zero Step 5 Add up the sum of the square roots this is your numerator now Step 6 Calculate denominator sample nl with n being your sample size pop is just N Step 7 Divide numerator amp denominator


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