1. Part II Sigma Freud & Descriptive Statistics
Chapter 4    
A Picture is Really Worth a Thousand Words

2. 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.

3. 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

4. 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

5. Histograms
Hand Drawn
Histogram

6. Histogram
Tally-Ho
Method

7. Frequency Polygon
A “continuous line that represents the frequencies of scores within a class interval”

8. Cumulative Frequency Distribution

9. Fat & Skinny of Frequency Distributions
Distributions can be different in four different ways…
Average value
Variability
Skewness
Kurtosis

10. Average Value

11. Variability

12. Skewness
Positive & Negative Skewness

13. Kurtosis
Platykurtic (A) & Leptokurtic (C)

14. Cool Ways to Chart Data
Column Chart

15. Cool Ways to Chart Data
Line Chart

16. Cool Ways to Chart Data
Pie Chart

17. Using the Computer to Illustrate Data
Creating Histogram Graphs

18. Using the Computer to Illustrate Data
Creating Bar Graphs

19. Using the Computer to Illustrate Data
Creating Line Graphs

20. Using the Computer to Illustrate Data
Creating Pie Graphs