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Chapter 6 Notes

by: Shannan Dillen

Chapter 6 Notes PSY 2110

Shannan Dillen
GPA 3.9

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About this Document

These notes over what the normal distribution is and how to use it in a data set.
Statistics for Behavioral Sciences
S. Tice-Alicke
Class Notes
Statistics, Math
25 ?




Popular in Statistics for Behavioral Sciences

Popular in Psychology (PSYC)

This 3 page Class Notes was uploaded by Shannan Dillen on Monday September 26, 2016. The Class Notes belongs to PSY 2110 at Ohio University taught by S. Tice-Alicke in Fall 2016. Since its upload, it has received 6 views. For similar materials see Statistics for Behavioral Sciences in Psychology (PSYC) at Ohio University.


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Date Created: 09/26/16
Chapter 4: Measures of Central Tendency Measure of Central Tendency – a score that summarizes the location of a distribution on a variable Locator – centrally located Ex: center of OU – College Green 3 measures – mean, median, and mode Important when communication measure of central tendency: 1. Type of data 2. Shape of distribution Mean – most widely reported measure -can be calculated when you have interval or ratio data -best measure of central tendency when distribution ???? – “x bar” – symbol for sample mean ???? = ∑X / n µ - “mu” – symbol for population mean µ = ∑X / N Median – exact midpoint of any distribution -ordinal, interval, or ratio data -best measure of central tendency when distribution is skewed th -always the score at the 50 percentile Uneven set of numbers 9 9 9 7 6 5 5 4 1 Median = 7 Even set of numbers 9 9 9 7 6 5 4 3 1 1 Median = 5.5 Mode – most frequently occurring score or scores in the distribution -nominal, ordinal, interval, and ratio data -only measure of central tendency for nominal data 6 5 4 5 3 2 5 2 Mode = 5 6 5 4 5 3 2 5 2 2 Mode = 5 and 2 Normal Distribution Mean = median = mode Measures of Variability -a score that indicates how spread out the scores are in a distribution -a measure of the distance between scores 1. Range – measurement of the width of the entire distribution Highest score – lowest score = 0 A B C 0 4 6 2 5 6 6 6 6 10 7 6 12 8 6 RA= 12 – 0 = 12 R = 8 – 4 = 4 B RC= 6 – 6 = 0 Range = 0, all values are the same Outlier – an extreme case; scores that stand apart from the rest of the distribution 2. Interquartile Range (IQR) – range of the middle 50% of the distribution -difference between score at 75 percentile and the score at the 25 percentile Order scores according to the magnitude first a) Find median b) Find median of the upper and lower halves c) Subtract these two scores for the IQR 3. Variance – the average of the square deviations of the scores around the mean 2 S = sample variance S = sample standard deviation Use the following population data set to calculate the following: µ, σ , σ X X2 12 144 10 100 10 100 9 81 8 64 8 64 7 49 6 36 6 36 4 16 2 4 2 4 μ = 7 σ = (698 – (84 /12)) / 12 = (698 – 588) / 12 = 110 / 12 = 9.17 σ = square root(9.17) = 3.03


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