1 Qualitative Data

1 Qualitative Data - Dr. Harvey A. Singer School of...

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© 2007 by Harvey A. Singer 1 OM 210:  Statistical Analysis for Management Data Presentation 1: Presenting Qualitative Data Dr. Harvey A. Singer School of Management George Mason University
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© 2007 by Harvey A. Singer 2 Topics List Data presentation introduction. Presenting qualitative data. Presenting quantitative data. Exploratory data analysis. Cross-tabulations and scatter diagrams. Cross-tabulations covered in probability, where they will be used. Scatter diagrams covered in regression, where they will be used.
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© 2007 by Harvey A. Singer 3 Data Presentation Purpose: The idea is to summarize sample data with pertinent and informative tables and charts. Fundamental principle: Sort the sample data into a number of distinct categories or “classes” and count the number of data per class. Compressing the many sample data into just a few distinct classes. Result: To see how the data is distributed and to recognize any patterns in the data. Generalize those patterns from the sample to the population.
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© 2007 by Harvey A. Singer 4 Data Presentation Main Tools: Frequency = the count of data per class. Relative frequency = the proportion or fraction of data per class. Additional tools: For ranked data, calculate “cumulatives.” Cumulative frequency = sum the frequency of a class and all preceding classes. How much of the data is up to and including a particular class. Cumulative relative frequency = sum the relative frequency of a class and all preceding classes. What fraction of the data is up to and including a particular class.
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© 2007 by Harvey A. Singer 5 Qualitative vs. Quantitative Data Similarities: Tools are the same for both data types. Differences: For qualitative data, the classes are obvious or logical. Suggested by the data. Classes are usually a “no-brainer.” Classes may be ranked or not, depending on the data. For numerical data, have to make the classes yourself. The classes are always numerically ranked. All discussed in the next presentation.
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© 2007 by Harvey A. Singer 6 Learning Objectives 1. Tabulate and display qualitative (categorical) data. Both nominal and ordinal data. 1. Organize numerical data. Whether discrete or continuous, whether interval or ratio data. 3. Tables and charts for numerical variables and data. 1. Graphing bivariate numerical data. 5. Good and bad data presentation.
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© 2007 by Harvey A. Singer 7 Tabulating and Graphing Qualitative Data Univariate Data Data collected for a single variable. Tabulate using a frequency distribution. Graph using a bar chart, a pie chart, or a Pareto diagram. Bivariate Data
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1 Qualitative Data - Dr. Harvey A. Singer School of...

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