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1. At the end of this lesson, the students will be able to: differentiate kinds of variables and their uses; do not compromise values and do the right thing even though face with criticism.

2. LESSON 3

3. Classification of Variables Numeric Variables Categorical Variables Experimental Variables

4. Variables is any factor or property that a researcher measures, controls, and/or manipulates. It is also the changing quantity or measure of any factor, trait, or condition that can exist in differing amounts or types. It is also a logical set of attributes, characteristics, numbers, or quantities that can be measured or counted. It is also called a data item.

5. Numeric Variables these are variables with values that describe a measurable numerical quantity and answer the questions “how many” or “how much”. These values are considered as quantitative data.

6. CONTINUOUS VARIABLES these variables can assume any value between a certain set of real numbers. The values depend on the scale used. Continuous variables are also called interval variables. Some examples are time, age, temperature, height, and weight.

7. DISCRETE VARIABLES these variables can only assume any whole value within the limits of the given variables. Some examples are the number of registered cars, number of business locations, number of children in the family, population of students, and total number of faculty members.

8. Categorical Variables these are variables with values that describe a quality or characteristics of a data unit like “what type” or “which category”.

9. ORDINAL VARIABLES these variables can take a value which can be logically ordered or ranked. Some examples are academic grades such as A,B,C; clothing size such as X,L,M,S; and measures of attitudes like strongly agree, agree, disagree, or strongly disagree.

10. NOMINAL VARIABLES these are variables whose values cannot be organized in a logical sequence. Some examples are business types, eye colors, kinds of religion, various languages, and types of learners.

11. DICHOTOMOUS VARIABLES these variables represent only two categories. Some examples are gender (male and female), answer (yes or no), and veracity (true or false).

12. POLYCHOTOMOUS VARIABLES these are variables that have many categories. Some examples are educational attainment (elementary, high school, college, graduate, and postgraduate), level of performance (excellent, very good, satisfactory, or poor).

13. Experimental Variables Independent Variables Dependent Variables Extraneous Variables

14. INDEPENDENT VARIABLES these are usually manipulated in an experiment. Thus, they are also called manipulated or explanatory variable.

15. DEPENDENT VARIABLES these variables are usually affected by the manipulation of the independent variables. They are also called response or predicted variables.

16. EXTRANEOUS VARIABLES these variables are also called mediating or intervening variables. These variables are already existing during the conduct of an experiment and could influence the result of the study. They are known as covariate variables.

17. 4. Variables according to the number being studied UNIVARIATE STUDY – only one variable is being studied BIVARIATE STUDY – two variables are being studied POLYVARIATE STUDY – more than two variables are being studied

18. Questions?