# Lecture 4.docx

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20 Apr 2012
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Lecture 4- January 31, 2012
Measures of Variability
Standard deviation conceptually, it is the degree of dispersion in a group of scores
Preferred measure of variability because of its direct relevance to the normal distribution
Variance squared value of the standard
Deviation
Figure 3.5- Skewed Distribution Curves
Skewness is one measure we use to tell us about the symmetry or asymmetry about the
distribution
One stretching to the left is lower scores (negative skew)
One stretching to the right is higher scores (positive skew)
When scores are at low end (positive skew), the test probably contains too few easy items
If scores are massed at the high end (negative skew) the test probably contains too few hard
items
Agreeableness- Normally Distributed?
People are higher than average in reporting agreeableness
Raw Score Transformations
The most basic level of information provided by a psychological test is the raw score
To be AT the first percentile is not a good thing in Psychology- it means you are at the very
bottom at the score
You want to be at the 99th percentile (this means your score is better than 99% of the
people)
T-scores and other standardized scores
T-score of 60 means they got through a lot of tasks, whereas a T-score of 20 means they
didn’t get through a lot of tasks
Measures of Central Tendency
Compute the mean by adding all the scores up and diving by N, the number of scores
The median is the middlemost score when all the scores have been ranked
Mode is the most frequently occurring score
If the scores are tightly packed around a central value, the SD is small
Figure 3.7
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