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