Graphs can effectively visualize data relationships but must be designed carefully. Bar charts and pie charts are appropriate for discrete categorical data. Bar charts compare frequencies as proportional bar widths and heights. Pie charts show category proportions through wedge sizes. Histograms and line graphs effectively display continuous and some ordinal data. Histograms use bar widths to represent value ranges. Line graphs connect data points to show trends over intervals. However, graphs can mislead if they distort data scales, use inappropriate or confusing designs, or include non-data elements. Data representation and readability should always be prioritized in graph creation.

1. Chapter 2 and Infographics ProjectGraphs: Good, Bad & Ugly

2. A visual presentation of dataRelationships & comparisons are visualLess daunting to some than tables of numbersAllows some artistry and creativityAccuracy is importantStyle of graph must matchScale (level) of measurement of the variable(s)Nature of this particular data setPurpose of a Graph

3. Graph that meets basic requirementsAxes drawn and labeled

4. Category values labeled

5. Title for graph

6. Data bars proportional to number of cases in data

7. Balanced

8. Maintains scale

9. No “chart junk”

10. Not complicated

11. Only one idea conveyedGraphs for Discrete Data(counts)Data are in categoriesNominal Ordinal (if few categories)Types of graph:Pie ChartBar Chart or Pictograph (Excel: Column chart)Show the Frequency (count) or Percent

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

13. The Bad:design hides trends or data

14. PICTOGRAPH: the Good bars constructed of equal size simple icons

15. PICTOGRAPH: the UglyElements of unequal sizeJust heads of some kidsAll children are playing except those from China – subtle racism

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

17. Practice: How many problems can you see in this graph?

18. PIE CHART: the AcceptableArea of pie = 100%Wedge is proportional to percentage of casesLabels show count or percent Ten slices is the maximum to remain clear & readable.

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

20. What can you detect in this old graph?

21. Graphs for Continuous Data (sometimes used for Ordinal data)Graph shows continuity of the constructHistogram: bars that touch at real limitsLine graph: covers range (a.k.a. Frequency Polygon)Horizontal axis goes from low to highIntervals shown for Interval or Ratio dataSome ordinal data also graphed this way(e.g., strongly agree, agree, slightly agree, etc)

22. Bar width is a rangeof scores or the reallimits of scores.Ranges equal widthLabels show mid-point or real limitsLow scores on left, high scores on rightHISTOGRAM: the Good

23. HISTOGRAM: the BadRanges of dataUnequal & indeterminateSpacing of “bars” is unequal.Water, sky, umbrella detract from graph

24. HISTOGRAM:the UglyCurved horizontal axis so no vertical axis.

25. Lowest categories are on the right, not left.

26. Intervals of income are unequal/indeterminate.

27. One interval is just plain wrong, and data are lost (all incomes $49,001 to $49,999 omitted).Same requirements as histogram.If more than one line,legend or labels are needed.More than four or fivelines can be hard tointerpretLine Graphs / Frequency Polygonfrom SRB Documentary. (2008). Demographic Winter: the Decline of the Human Family at http://www.demographicwinter.com/index.html

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

29. Modern graphs have more optionsThe Future of Food. (2008) WiredMagazine 16:11

30. Chapter 2 and Infographics ProjectGraphs: Good, Bad & Ugly