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Categorical and Continuous Variables

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Categorical and Continuous Variables
By
SSG Huerta Aracely
18 July 2015
MHS 506 Biostatistics

Categorical and Continuous Variables
Variables and data can either represent measurements on some continuous scale, or they represent information about some categorical or discrete characteristics. Some examples of continuous variable are weight, height, and age. Categorical variables can be considered a person's gender, occupation, or marital status. Some variables could be considered both categorical and continuous variables. One example of this type of variable is a person's rating of someone else's attractiveness on a 4 point scale.
Categorical Variables Categorical variables represent types of data which may be divided into groups. Examples of categorical variables are race, sex, age group, and educational level. While the latter two variables may also be considered in a numerical manner by using exact values for age and highest grade completed, it is often more informative to categorize such variables into a relatively small number of groups. Analysis of categorical data generally involves the use of data tables. A two samples or measures presents categorical data by counting the number of observations that fall into each group for two variables, one divided into rows and the other divided into columns. For example, a survey to identify their hair and eye color.
Continuous Variables Much of the statistical analysis in medical research involves the analysis of continuous variables such as cardiac output, blood pressure, and heart rate which can assume an infinite range of values. As with discrete variables, the statistical analysis of continuous variables requires the application of specialized tests. These tests compare the means of two or more data sets to determine whether the data sets differ significantly from one another. There are four

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