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## PSY 138 Notes for 8/31 & 9/2

by: Morgan Bertalon

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0

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# PSY 138 Notes for 8/31 & 9/2 PSY 138

Marketplace > Illinois State University > PSY 138 > PSY 138 Notes for 8 31 9 2
Morgan Bertalon
ISU
GPA 3.6
Reasoning in Psychology Using Statistics
D. Ispas

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These are the notes for PSY 138 8/31 and 9/2. They cover vocabulary, Sum of Squared Deviations, Variance and Standard Deviation, and Biased and Unbiased Estimators.
COURSE
Reasoning in Psychology Using Statistics
PROF.
D. Ispas
TYPE
Class Notes
PAGES
3
WORDS
KARMA
25 ?

## Popular in Department

This 3 page Class Notes was uploaded by Morgan Bertalon on Sunday September 6, 2015. The Class Notes belongs to PSY 138 at Illinois State University taught by D. Ispas in Fall 2015. Since its upload, it has received 10 views.

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Date Created: 09/06/15
Reasoning in Psychology Using Statistics 138 Notes for 831 amp 92 0 Central Tendency single score used to de ne center of distribution Discrete variable indivisible 0 Ex can39t have 22 children Continuous variable in nitely divisible Population all individuals of interest Sample subset of population Parameter describes a population Statistic describes a sample 1 Mean a Balance point b Measures distance from center C EX 2253 3 2 Weighted mean a Take mean from two separate samples add both means together then add the number of variables from the two samples Divide added means and added variable amounts b Ex X1 X2n1 n2 3 NOIR a Nominal data i Categories ex democrats or republicans b Ordinal data i Ordered categories ex 1 2nd 3rd c Interval data i Ordered but has set interval and no true zero ex temperature in Celsius d Ratio data i Ordered has set intervals true zero ex weight 4 Median a Extreme scores b Undetermined scores c Openended category d Ordinal data 5 Mode a Discrete variables b Nominal data Measures of Variabilitv 1 Why look at variability a Describes distribution i Are scores close together ii Spread out 2 Variability a Degree to which scores vary spread out or clustered 3 Range a Difference between largest value and smallest value b Problem impacted by extreme scores c Ex range 40139 not representative of data d Only based on two scores 4 Deviation Distance from the mean Computed for each score Difference between each score and mean Sum of deviation is ALWAYS zero 2 Xll 0 Sum of Squared Deviations 0qu9 1 Compute deviation 2 Sums of deviations is always zero 3 Square deviations 4 Then add together sum of squared deviations 5 Ex Xu2 Variance and Standard Deviation 1 Variance average squared distance from mean 2 Standard deviation measure of average distance from mean 3 Standard deviation is most commonly used and the most important measure of variability 4 Slight calculation differences between populations and samples 5 Symbols a Population variance sigma squared 02 b Population standard deviation sigma o c Sample variance 52 d Sample standard deviation 5 or SD Process Population 1 Find deviation 2 Square each deviation 3 Find average of squared deviation variance Compute Pooulation 1 Compute deviation from mean of each score 2 Square each deviation score Computing Sample Variance 1 Similar process 2 Use different notation n M s 3 One difference to get variance sum of square deviation is divided by n1 instead of N in pop Biased and Unbiased Estimators 1 Samples to populations 2 Sample values will be different than population values 3 Mean is unbiased Standard deviation is biased estimator sample variance will underestimate population variance That39s why we divide by n1 when calculating sample variance and standard deviation

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