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Slides for lecture on basic graph types for a statistics class.

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- 1. Chapter 2 and Infographics Project<br />Graphs: Good, Bad & Ugly<br />
- 2. A visual presentation of data<br />Relationships & comparisons are visual<br />Less daunting to some than tables of numbers<br />Allows some artistry and creativity<br />Accuracy is important<br />Style of graph must match<br />Scale (level) of measurement of the variable(s)<br />Nature of this particular data set<br />Purpose of a Graph<br />
- 3. Graph that meets basic requirements<br /><ul><li>Axes 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 conveyed</li></li></ul><li>Graphs for Discrete Data(counts)<br />Data are in categories<br />Nominal <br />Ordinal (if few categories)<br />Types of graph:<br />Pie Chart<br />Bar Chart or Pictograph (Excel: Column chart)<br />Show the Frequency (count) or Percent<br />
- 12. Area of bars combined is 100%<br />Area of each bar is proportional to its percent of total<br />Bars do not touchbecause categoriesare discrete.<br />Many variations; this is the most simple.<br />BAR CHART: the Good<br />
- 13. The Bad:design hides trends or data<br />
- 14. PICTOGRAPH: the Good bars constructed of equal size simple icons<br />
- 15. PICTOGRAPH: the Ugly<br />Elements of unequal size<br />Just heads of some kids<br />All children are playing except those from China – subtle racism<br />
- 16. BAR CHART – problems to consider:area, color – & why is that jogger there?<br />
- 17. Practice: How many problems can you see in this graph?<br />
- 18. PIE CHART: the Acceptable<br />Area of pie = 100%<br />Wedge is proportional to percentage of cases<br />Labels show count or percent <br />Ten slices is the maximum to remain clear & readable.<br />
- 19. PIE CHART: the Badcharts confuse or obscure the pattern in the data<br />
- 20. What can you detect in this old graph?<br />
- 21. Graphs for Continuous Data (sometimes used for Ordinal data)<br />Graph shows continuity of the construct<br />Histogram: bars that touch at real limits<br />Line graph: covers range (a.k.a. Frequency Polygon)<br />Horizontal axis goes from low to high<br />Intervals shown for Interval or Ratio data<br />Some ordinal data also graphed this way(e.g., strongly agree, agree, slightly agree, etc)<br />
- 22. Bar width is a rangeof scores or the reallimits of scores.<br />Ranges equal width<br />Labels show mid-point or real limits<br />Low scores on left, high scores on right<br />HISTOGRAM: the Good<br />
- 23. HISTOGRAM: the Bad<br />Ranges of data<br />Unequal & indeterminate<br />Spacing of “bars” is unequal.<br />Water, sky, umbrella detract from graph<br />
- 24. HISTOGRAM:the Ugly<br /><ul><li>Curved 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).</li></li></ul><li>Same requirements as histogram.<br />If more than one line,legend or labels are needed.<br />More than four or fivelines can be hard tointerpret<br />Line Graphs / Frequency Polygon<br />from SRB Documentary. (2008). Demographic Winter: the Decline of the Human Family at http://www.demographicwinter.com/index.html<br />
- 28. LINE GRAPH: the Bad<br />Why is the headline “Steady growth” for this graph?<br />Hint: check the axis values<br />If it is growth, is it steady ?<br />Hint: how did each of the three variables change from 1988 to 1989.<br />
- 29. Modern graphs have more options<br />The Future of Food. (2008) WiredMagazine 16:11<br />
- 30. Chapter 2 and Infographics Project<br />Graphs: Good, Bad & Ugly<br />

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