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## Behavior & Statistics 5

by: Alexis Notetaker

26

0

1

# Behavior & Statistics 5 Psychology 211

Alexis Notetaker
SIU
GPA 3.0

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These notes are pretty short as well so I hope they can be of use to some of you but, the next set of notes should be more informative.
COURSE
Behavioral Statistics
PROF.
Zachary Pilot
TYPE
Class Notes
PAGES
1
WORDS
CONCEPTS
Psychology
KARMA
25 ?

## Popular in Psychlogy

This 1 page Class Notes was uploaded by Alexis Notetaker on Monday February 29, 2016. The Class Notes belongs to Psychology 211 at Southern Illinois University Carbondale taught by Zachary Pilot in Spring 2016. Since its upload, it has received 26 views. For similar materials see Behavioral Statistics in Psychlogy at Southern Illinois University Carbondale.

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Date Created: 02/29/16
Psy Notes 5 Monday, February 22, 201611:45 AM Central Tendency • Describes the central point Variability • Quantitative measure of difference between a set of scores • Describes how spread out the scores are in distribution ○ Provides a measure of how accurately any individual score or sample represents the entire population • Inferential Variability ○ Can be small or large  Small □ One score/sample can fairly represent the population  Large □ A few outliers may distort the picture of the general population ○ Inferential statistics are used to detect patterns and variability influences how easily they are detected Measures • Range ○ The total distance covered by the distribution, from highest to lowest score  Range = max -min SD Calculation Summary • Mean = 600 + 470+ 170+430+300/5=1970/5=394 ○ Mean = 394  206^2=42436  -224^2=50176  76^2=5776  -94^=8836  36^2=1296 □ 42436+50176+5776+8836+1296=108520  108520/5=21704  So the variance is 21704 ◊ So square root 21704=14.32 ◊ So SD equals 147.32  Population data Formulas • Population ○ Variance = o = sqrt SS/N Unbiased and Biased Statistics • Unbiased ○ The average value is equal to the population parameter ○ Parameter  Measure that describes a population • Biased ○ The average value overestimates or underestimates the corresponding population parameter

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