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Why?

To get an overview and summary of a dataset

How?

Get a grasp of the integrity of your dta. Eliminate bogus data-points. Summarize your data with appropriate tables such as counts, frequency charts, means and standard deviation and graphs such as box-plots and bar and pie charts. Try to get a global sense of what your data is telling you.

Ingredients

• A well-defined dataset
• Statistical software such as SPSS, R of Excel.
• Basic knowledge about statistics and probability theory
• A keen eye for the difference between signal and noise.

In practice

All statistical analyses should start with descriptive statistics. They give researchers a feel for the data and data integrity. Sometimes, descriptive statistics are sufficient to answer the research questions. In other cases, they are a necessary prerequisite for inferential statistics.

Phase(s) of use

In the following project phase(s) descriptive statistics can be used:

• Problem definition
• Analysis