Focus on graphs for describing data, with a quick overview of central tendency and variability

1. Descriptive Statistics PSY 330 Research Methods

2. Measurements Choices Determine Analysis Options Choice of measure occurs in research design Measures yield data at a particular scale (level) of measurement (Nominal, Ordinal, Interval, Ratio) Interval or Ratio data can be “recoded” to create groups (e.g., age groups, income ranges) Grouped data cannot be expanded to create Interval or Ratio data Scale (Level) of Measurement determines which techniques are appropriate.

3. Matching Average to Data

4. Matching Variability Measure to Data Range and Interquartile Range (IQR) use only a few scores. Standard deviation and variance use the value of each score in the data set Range and IQR are related to Median Standard Deviation and Variance are related to the Mean.

5. Purpose of a Graph A visual presentation of data Relationships & comparisons are visual Less daunting to some than tables of numbers Allows some artistry and creativity Accuracy is important Characteristics of data Measurement choices in design determine analysis choices later Scale (level) of measurement determines which graphs can be used Nature of the particular data set is also important

6. Graphs for Complex Data The Future of Food. (2008) WiredMagazine 16:11 From ChoiceRanker website via JunkCharts blog at http://junkcharts.typepad.com/junk_charts/2008/07/its-raining-colors-here-too.html

8. Category values labeled

9. Title for graph

10. Data bars proportional to number of cases in data

11. Balanced

12. Maintains scale

13. No “chart junk”

14. Not complicated

16. BAR CHART: the Good Area of bars combined is 100% Area of each bar is proportional to its percent of total Bars do not touchbecause categoriesare discrete. Many variations; this is the most simple.

17. The Bad:design dominatestrends or data

18. PICTOGRAPH: the Good bars constructed of equal size pictures

19. PICTOGRAPH: the Ugly Elements of unequal size Just heads of some kids All children are playing except those from China – subtle racism

20. BAR CHART – problems to consider:area, color – & why is that jogger there?

21. PIE CHART: the Good Area of pie = 100% Wedge is proportional to percentage of cases Labels show count or percent Ten slices is the maximumto remain clear

22. PIE CHART: the Badcharts confuse or obscure the pattern in the data

23. Graphs for Continuous Data (sometimes Ordinal) Graph shows continuity of the construct Histogram: bars that touch at real limits Line graph: covers range (a.k.a. Frequency Polygon) Horizontal axis goes from low to high Intervals shown for Interval or Ratio data Some ordinal data also graphed this way(e.g., strongly agree, agree, slightly agree, etc)

24. HISTOGRAM: the Good Bar width is a rangeof scores or the reallimits of scores. Ranges equal width Labels show mid-point or real limits Low scores on left, high scores on right

25. HISTOGRAM: the Bad Ranges of data Unequal Indeterminate Spacing of “bars” is unequal. Water, sky, umbrellaall detract from graph

26. Line Graphs / Frequency Polygon Same requirements as histogram. If more than one line,legend or labels are needed. More than four or fivelines can be hard tointerpret from SRB Documentary. (2008). Demographic Winter: the Decline of the Human Family at http://www.demographicwinter.com/index.html

27. LINE GRAPH: the Bad Why is the headline “Steady growth” for this graph? Hint: check the axis values If it is growth, is it steady ? Hint: how did each of the three variables change from 1988 to 1989.

28. Interesting trends in graphs:Population Map Area=population, displayed by location.

29. World Mapper ProjectA collection of world maps, where territories are re-sized according to the subject of interest. Internet Users in 2002

30. World Mapper Projecthttp://www.worldmapper.org/ Alcohol Consumption 2006

31. Descriptive Statistics PSY 330 Research Methods