Descriptive Statistics

Descriptive statistics involves organizing, summarizing and illustrating statistical data. The objective is to show important characteristics of the data without drawing any conclusions.

Inferential statistics involves using a representative subset of data (a sample) in order to draw conclusions about unknown characteristics of an entire set of data (a population).

Population:

The entire set of elements of interest (i.e. all humans, all working-age people in Canada, all IT companies). A population parameter is a characteristic used to describe a population. For example,

Population mean (
Population standard deviation (
Population median (

The values of the population parameters would be preferable for use in decision-making but seldom will these values be known since collecting all the population elements (a census) is usually too expensive and/or time consuming.

Sample:

A representative subset of the entire set of elements of interest that is used to gain insight about the population. A sample statistic is a characteristic used to describe a sample. For example,

Sample mean [pic]
Sample standard deviation s
Sample median Md

It is cheaper, less time-consuming and more practical to use sample statistics as estimates for population parameters in making business decisions. How well the sample represents the population depends on the sample design.

Using Samples to Describe Populations:

The following data consists of two samples of house prices, one sample selected from the city of Montreal and the other selected from the West Island:

|Descriptive Statistics - Montreal |
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