TABLE OF CONTENTS Data present information about a product or process. The data may be qualitative or quantitative. In any project/process, effective presentation of the data is as important as the collection of the data. Weeding out irrelevant information and conveying all relevant information accurately and unambiguously are also important. Because data may support or reject project objectives, data become a very critical part of any project or process.
Numerous data presentation techniques are available to describe data. Some commonly used techniques will be described:
Tables, histograms, and box plots describe both the central tendency and the distribution of data.
Bar graphs and stacked bar graphs compare information from different sources.
Pie charts proportionate the distribution relationship in the data (information).
Line graphs, control charts, and run charts describe data (information) changes over time.
Mean, median, and mode describe the central tendency of data.
Range, variance, and standard deviation describe data distribution.
As a project team analyzes the data, the team must determine which data properties that support project issues/problems are dominant in the collected/historical data:
If the team is looking for "What is the central tendency of the data?" and/or "Where do the values tend to occur?" then the team should analyze the data for mean, median, and mode.
If data distribution (dispersion) is the team's interest, then the team should analyze the data for range, variance, and standard deviation and try to summarize the information in tables, histograms, and box plots.
If the team is interested in...
