Central Tendency, Dispersion, and Visualizing Data Flashcards
three measures of central tendency
mean, median, mode
mode
most frequent occurring in the data
pros of mode
- best if data is nominal
- if rough estimate needed
- its a number in your data set
cons of mode
- small samples may not have a mode
- ignores most of the information in a distribution
median
the score that divides the distribution in half
median is used when
- variables are measured with open ended distributions
- extreme scores (outliers)
mean
mean is the average
mean pros
- best with interval/ratio data
- does not ignore any data
- symmetric distributions
- used in inferential statistics
mean cons
- misleading for highly skewed distributions
- the number is likely not in your distribution
variation ratio (VR)
VR = 1 - % of cases in the mode
interquartile range (IQR)
Q3 - Q1
what does a quartile represent
specific scores in the distribution
Q1 25%
Q2 50%
Q3 75%
Q2 is the _____ value
median
strengths of IQR
- not effected by extreme scores
- reasonably stable
- easy to compute
weakness of IQR
- limited use: descriptive purposes only
- ignores the upper and lower 25%
standard deviation (SD)
describes the average distance of the values from their mean
large SD
- less consistency in the data
- data might be more suspect due to large degree of dispersion through the mean
small SD
- more consistency in the data
- less dispersion through the mean
