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Chapter 5

PSYC 210 Chapter Notes - Chapter 5: Linear Map, Standard Deviation, Conditional Probability

Department
Psychology
Course Code
PSYC 210
Professor
Cathy Mc Farland
Chapter
5

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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 long-range 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
Box-and-whisker 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
- 
H-spread 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
H-spread 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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