Part II
Sigma Freud & Descriptive Statistics
Chapter 4    
A Picture is Really Worth a Thousand
Words
Why Illustrate Data?
 When describing a set of scores you will want
to use two things…
 One score for describing the group of data
 Measure of Central Tendency
 Measure of how diverse or different the scores
are from one another
 Measure of Variability
 However, a visual representation of these two
measures is much more effective when
examining distributions.
Ten Ways to a Great Figure
 Minimize the “junk”
 Plan before you start creating
 Say what you mean…mean what you say
 Label everything
 Communicate ONE idea
 Keep things balanced
 Maintain the scale in the graph
 Remember…simple is best
 Limit the number of words
 The chart alone should convey what you
want to say
Frequency Distributions
 Method of tallying, and representing the
number of times a certain score occurs
 Group scores into interval classes/ranges
 Creating class intervals
 Range of 2, 5, 10, or 20 is usually good
 10-20 class intervals for the entire range of data
 Divide total # of data points by # of class
intervals desired to determine numeric range of
the class intervals
Histograms
 Hand Drawn
Histogram
Histogram
 Tally-Ho
Method
Frequency Polygon
 A “continuous line that represents the
frequencies of scores within a class
interval”
Cumulative Frequency Distribution
Fat & Skinny of Frequency Distributions
 Distributions can be different in four different
ways…
 Average value
 Variability
 Skewness
 Kurtosis
Average Value
Variability
Skewness
 Positive & Negative Skewness
Kurtosis
 Platykurtic (A) & Leptokurtic (C)
Cool Ways to Chart Data
 Column Chart
Cool Ways to Chart Data
 Line Chart
Cool Ways to Chart Data
 Pie Chart
Using the Computer to Illustrate Data
 Creating Histogram Graphs
Using the Computer to Illustrate Data
 Creating Bar Graphs
Using the Computer to Illustrate Data
 Creating Line Graphs
Using the Computer to Illustrate Data
 Creating Pie Graphs