Looking at Data--Distributions
Introduction, Displaying Distributions with Graphs
Describing Distributions with Numbers
Learning goals for this chapter:
Identify categorical and quantitative variables.
Interpret, create (by hand and with SPSS), and know when to use:
bar graphs, pie
charts, stemplots (standard, back-to-back, split), histograms, and boxplots
(regular, modified, side-by-side).
Describe the shape, center, and spread of data distributions.
Define, calculate (by hand and with SPSS), and know when to use measures of
center (mean vs. median) and spread (range, 5-number summary, IQR, variance,
Understand what a resistant measure of center and spread is and when this is
Use the 1.5IQR rule to look for outliers.
Draw a Normal curve in correct proportions and identify the mean/median,
standard deviation, middle 68%, middle 95%, and middle 99.7%.
Perform calculations with the empirical rule, both backwards and forwards.
Understand the need for standardization.
what do we learn in this chapter?
(quantitative variables—good for checking for
symmetry and skewness)
(quantitative variables—graphical display of the 5 # summary, modified
boxplots show outliers)
(mean or median)
(usually standard deviation/variance or IQR from the 5 # summary)
If you have a symmetric distribution with no outliers, use the mean and standard
If you have a skewed distribution and/or you have outliers, use the 5 # summary