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Chapter 5
PSYC 210 Chapter Notes  Chapter 5: Linear Map, Standard Deviation, Conditional Probability
by OC24234
School
Simon Fraser UniversityDepartment
PsychologyCourse Code
PSYC 210Professor
Cathy Mc FarlandChapter
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PSYC 210
CHAPTER 5 – MEASURES OF VARIABILITY (p. 75)
Variability / Dispersion – the degree to which individual data points are distributed around the mean
Range (R) – the distance from the lowest to the highest score
 R = highest number – lowest number
 Total reliance on extreme values
Interquartile Range – the range of the middle 50% of the observations
 Discards the lower and upper 25% of the distribution
 If it discards too much data then it is not a very good estimate of the overall variability
 Trimmed Samples – samples with a percentage of the extreme scores removed
 Trimmed Statistics – statistics calculated on trimmed samples
Variance
 Mean absolute deviation (m.a.d.) – the average of the absolute values of the deviations from the
mean
 Sample Variance (s2) – sum of the squared deviations about the mean divided by N – 1
o
 Population variance (σ2) – variance of a population; usually an estimate, rarely computed
Standard Deviation (SD, s or σ) – the square root of the variance

Bias – a property of a statistic whose longrange average is not equal to the parameter it estimates
Expected Value or E() – the long range average of a statistic over repeated samples
Boxplot – a graphical representation of the dispersion of a sample
Boxandwhisker plot – a graphical representation of a sample
Hinges (quartiles) – those points that cut off the bottom and top quarter of a distribution
Quartile location – the location of the quartile in an ordered series

Hspread – the range between the two hinges (also the interquartile range)
Whisker – line from the top and bottom of the box to the farthest point that is no more than 1.5 times the
Hspread from the box
***see page 91***
Winsorized Variance – the variance of a winsorized sample
Winsorized Sample – a sample in which trimmed observations are replaced with the highest and lowest
values
CHAPTER 6: THE NORMAL DISTRIBUTION
Why the normal distribution is important
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