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DATA ANALYSIS - PowerPoint PPT Presentation

DATA ANALYSIS. GRAPHS Graphs are easy to read, and highlight distribution’s shape. The are useful because they show the full range of variation and identity data anomalies that might be in need of further study. Most common are bar charts, histograms, and frequency polygon.

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GRAPHS

• Graphs are easy to read, and highlight distribution’s shape. The are useful because they show the full range of variation and identity data anomalies that might be in need of further study.

• Most common are bar charts, histograms, and frequency polygon.

Important Guidelines Regarding Graphs representing the number or percentage of cases with each value. This is an alternative to the histogram when the distribution of quantitative, continuous variable must be displayed.

• Begin the graph of a quantitative variable at 0 on both axes.

• Always use bars of equal width.

• The two axes (X and Y) should be of approximately equal length.

• Avoid chart junk that can confuse the reader and obscure the distribution’s shape.

FREQUENCY DISTRIBUTION Bar char showing gender distribution.

• A frequency distribution displays the number, percentage (the relative frequencies), or both of cases corresponding to each of a variable’s values or group of values.

Death Penalty Statutes 1993 Bar char showing gender distribution.

Source: Kathleen Maguire and Ann L. Pastore, eds., Sourcebook of Criminal Justice Statistics. 1994. U.S. Department of Justice, Bureau of Justice Statistics. Washington, D.C.: U.S. Government Printing Office, 1995, pp. 115-116.

Creating a Frequency Distribution Bar char showing gender distribution.

Frequency

1

1

9

4

12

Total N 27

Minimum Age Tally

14 |

15 |

16 |||||||||

17 ||||

18 ||||||||||||

Creating a Frequency Distribution Bar char showing gender distribution.

Minimum Age Frequency

14 1

15 1

16 9

17 4

18 12

Total N 27