• ## Summary

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• 00:04

[Understanding Different Types of Variables]

• 00:11

SPEAKER: A variable is anything phenomenon or characteristicthat can change from case to casein your quantitative research.This can be anything from a political opinionto an observable behavior or type of visual representation.Variables may be observed, surveyed,or otherwise measured.And once captured, they can be subjectedto statistical analysis.

• 00:33

SPEAKER [continued]: Your quantitative data can take the formof three different types of variables.You must be able to identify these different typesof variables in order to choose the appropriate statisticalanalysis.[First Type: Categorical Variable]The first type of variable is called a categorical variable.A categorical variable has two or more categories.But there is no intrinsic ordering to the categories.

• 00:54

SPEAKER [continued]: For example, you can't calculate an averagefor people of different sexual orientations, genders,ethnicities, or hair colors.People with blonde, red, or black hair,are simply in different categories.Other examples of categorical variablesinclude gender, male or female, placeof birth, native born or immigrant,and marital status-- married or single.

• 01:18

SPEAKER [continued]: Remember that categorical data is sometimescalled nominal data.[Second Type: Ordinal Variable]A second type of variable is called an ordinal variable.The categories in an ordinal variablehave a clear, natural ordering.For example, the categories of social class and educationlevel are clearly ordered from lower to higher.And they must remain in this order.

• 01:40

SPEAKER [continued]: However, even though the categories within each variablecan be ordered, the spacing between each categoryis not equal with ordinal data.For example, the size of the step from working classto middle class is not necessarilythe same in terms of income, as the step from middle classto upper class.Likewise, the step from bachelor's degreeto master's degree is not the same as the step from master'sto a doctorate.

• 02:07

SPEAKER [continued]: This makes education level an ordinal variable.[Third Type: Interval Variable]The third type of variable is called an interval variable.An interval variable has a natural structure,such as from low to high, just as an ordinal variable.The difference is that the spacesbetween the categories of an interval variable are equal.For example, annual income measured in US dollarswould be interval data because the step from $1 to$2is the same as the step from $125 to$126, and so on.

• 02:39

SPEAKER [continued]: There is always the same interval, or space,between each value within the variable.The same goes for age measured in years.Interval data is sometimes also calledcontinuous or scaled data.Variable types matter because particular statistical analysesare intended for use with only certain types of variables.

• 03:01

SPEAKER [continued]: For example, you can't compute an average level of hair colorin a room full of people because the statistical calculationof the arithmetic average requires an interval variable.And hair color is a categorical variable.If you want to understand the relationship between twocategorical variables, such as gender and job category,you would use a chi-square statistical test.

• 03:24

SPEAKER [continued]: You can also use the chi-square testto analyze the relationship between one categorical and oneordinal variable, such as gender and education level, or twoordinal variables, such as educationlevel and social class.However, if your research takes you down a different pathand you decide to collect interval data-- for example,about age and weekly income-- youcould use a Pearson's correlation analysisto examine the relationship between these two variables,if some assumptions about the data are confirmed.

• 03:53

SPEAKER [continued]: Interval data also allows you to calculate an arithmetic averageand to use statistical tests built on averages.The main thing to remember is that your choicesabout what type of data to collectwill affect the types of statistical analysisthat are available to you later in the quantitative dataanalysis process.

### Video Info

Publisher: SAGE Publications Ltd.

Publication Year: 2017

Video Type:Tutorial

Methods: Types of variable

### Segment Info

Segment Num.: 1

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## Abstract

Dr. Charles Laurie and Dr. Eric Jensen discuss the different types of variables and how they relate to one another. Categorical, ordinal, and interval variables are explained.