The data below represents values of a variable. The variable represents the number of minutes college students spend on line each day.
13 54 10 03 16 20 17 40 04 02
07 25 08 21 19 15 03 17 14 06
12 45 01 08 04 16 11 18 23 12
06 02 14 13 07 15 46 12 09 18
34 13 41 28 36 17 24 27 29 09
14 26 10 24 37 31 08 16 12 16
It would be very difficult to glean any useful information from this data in its present form. Techniques have been developed for transforming raw data into a form that enables one to understand, visualize, and interpret data. These techniques are collectively referred to as Descriptive statistics and are listed below.
The idea of central tendency is to represent the given data by a single value that represents the entire data set. There are three measures of central tendency that are used extensively in statistics:
No doubt you have seen a major TV network announce the winner of a presidential election long before all the polls were closed. How can this be done? The networks were able to use a very small sample of all voters and from this sample make an inference about the choice of all voters regarding the candidates. Inferential statistics is that branch of statistics in which researchers are able to draw conclusions from small groups of subjects called samples, to larger groups called population. Often populations are very large which means that it would be expensive and time consuming to poll each member of a group. Statistical techniques have been developed which enable researchers to make inferences about the population from a sample of the population. See Sampling chapter I.