Descriptive statistics enable us to understand data through summary values and graphical presentations. Summary values not only include the average, but also the spread, median, mode, range, and standard deviation. It is important to look at summary statistics along with the data set to understand the entire picture, as the same summary statistics may describe very different data sets. Descriptive statistics can be illustrated in an understandable fashion by presenting them graphically using statistical and data presentation tools.
When creating graphic displays, keep in mind the following questions:
Several types of statistical/data presentation tools exist, including: (a) charts displaying frequencies (bar, pie, and Pareto charts, (b) charts displaying trends (run and control charts), (c) charts displaying distributions (histograms), and (d) charts displaying associations (scatter diagrams).
Different types of data require different kinds of statistical tools. There are two types of data. Attribute data are countable data or data that can be put into categories: e.g., the number of people willing to pay, the number of complaints, percentage who want blue/percentage who want red/percentage who want yellow. Variable data are measurement data, based on some continuous scale: e.g., length, time, cost.
|To Show||Use||Data Needed|
Frequency of occurance: Simple percentages or comparisons of magnitude
|Tallies by category (data can be attribute data or variable data divided into categories)|
|Trends over time||
|Measurements taken in chronological order (attribute or variable data can be used)|
|Distribution: Variation not related to time (distributions)||Histograms||Forty or more measurements (not necessarily in chronological order, variable data)|
|Association: Looking for a correlation between two things||Scatter diagram||Forty or more paired measurements (measures of both things of interest, variable data)|