PSYC 331 Lecture 11 -- Variability

PSYC 331 Lecture 11 -- Variability - PSYC 331 Lecture 11...

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1 PSYC 331 Lecture 11 Variability
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2 Overview In this lecture we will cover Descriptions of distributions Measures of variability Range Inter-Quartile Range Standard Deviation Calculations the sum of squares (SS), standard deviation and variance for A population A sample Graphs of variability
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3 Description of a Distribution Four characteristics of the distribution are needed for a complete description of a distribution: a) central tendency b) variability c) skewness d) kurtosis
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4 Variability Variability -- "spread" of the scores in a distribution. Are the scores clustered close together, or are they very dispersed? (Note that all have n=1000 and M= 100)
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5 Measures of Variability There are several measures of variability available for use, including Range Interquartile Range Standard Deviation
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6 Range The highest score URL minus the lowest score LRL Or, when the scores are whole numbers, the range is (highest X – lowest X) +1 Easy to determine, but very rough estimate of variability. Problems with range: Influenced by just two scores Sample range is almost always < population range Not usable for inference
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7 Inter-Quartile Range Same basic idea as the range Computed using percentile scores Provides an estimate of the "typical" distance from the median Problems: Not usable for inference Computed by: 75 th percentile score – 25 th percentile score (Which is the same as: 3 rd quartile score – 1 st quartile score) Use interpolation to find the 75 th and 25 th percentiles!
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8 Standard Deviation The most common measure of variability as it is the only one of the three that is usable for inference.
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9 What does Standard Deviation Measure? A
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PSYC 331 Lecture 11 -- Variability - PSYC 331 Lecture 11...

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