# Use of Descriptive Statistics over Inferential Statistics

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Q1. When would you use descriptive over inferential statistics? Provide a specific scenario and explain your rationale.
"Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data" (Understanding descriptive and inferential statistics, 2012, Laerd). Examples of descriptive statistics include an analysis of central tendency (the position of most members of the group in a particular category, such as age) and measures of spread (the range of members of a group, such as in terms of their various ages). Inferential statistics are often used when not all members of the group can feasibly be tested. "Inferential statistics are techniques that allow us to use these samples to make generalizations about the populations from which the samples were drawn," although the sample must accurately represent the population (Understanding descriptive and inferential statistics, 2012, Laerd). "Both descriptive and inferential statistics rely on the same set of data. Descriptive statistics rely solely on this set of data whilst inferential statistics also rely on this data in order to make generalisations about a larger population" (Understanding descriptive and inferential statistics, 2012, Laerd).
For a small organization, using descriptive statistics might be feasible, given the size of the client base. Also, fewer resources might be used in the long run than