LESSON 6: KINDS, NATURE AND TYPES OF VARIABLES

By margarettepearlsibayan | Updated: Oct. 13, 2021, 9:32 p.m.

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HI! MY NAME IS
 MS. MARGARETTE
LESSON 6:

KINDS, NATURE AND TYPES OF VARIABLES
WHAT IS VARIABLES?

are “changing qualities or characteristics” of persons or things like age, gender, intelligence, ideas, achievements, confidence, and so on that are involved in your research study. Made up of the root or base word “vary” which means to undergo changes or to differ from, variables have different or varying values in relation to time and situation. For instance, as years go by, your age or intelligence increases. But placed in a situation where you are afflicted with a disease or have no means of reading or no access to any sources of knowledge, your intelligence tends to decrease. (Suter 2013, p. 137)  
EXPLANATION: 
- measurable characteristics that has value 
- entity (pagkakakilanlan) that can take in different values 
- aspect of theory that can VARY OR CHANGE 
- anything that can AFFECT OR CHANGE THE RESULT OF THE STUDY

EXAMPLES: 1. Work Status – Self Employed, Government Employed, Private Employed, Others
REMEMBER: VARIABLE IS IN DIFFERENT FORM SUCH AS;

1. age 
2. gender 
3. IQ level 
4. lifestyle 
5. temperature
 6. Medical treatment used
VARIABLE CAN BE CLASSIFIED AS;
(these are classified as the role of different variables in the study)

 NUMERICAL  
CATEGORICAL  
EXPERIMENTAL 
 NON-EXPERIMENTAL  
NUMERICAL VARIABLES

- has values that describe a MEASURABLE NUMERICAL quantity 
- Quantitative data in nature 
- It answers the questions HOW MANY AND HOW MUCH?

QUANTITATIVE VARIABLES – variables that can be obtained through counting and can reflect notion of magnitude. (It can be weak, moderate or strong). It can be expressed in numbers (they are measured or quantify)  
TYPES OF NUMERICAL VARIABLES

1. CONTINUOUS/INTERVAL VARIABLE 
- A variable that can take infinite number on the value that can occur within the population. Its values can be divided into fractions. 
 Examples of this type temperature (Celsius and Fahrenheit)

Explanation: 
 - Assume any value BETWEEN certain set of real numbers depending on scales used. 
 - Variable has an infinite (having no limits) number of possibilities 
- Using units for measurement, has a possibility that has a decimal in data 
- can be fractions 
- Non-whole numbers 
- take either positive or negative value 
TYPES OF NUMERICAL VARIABLES

A. RATIO VARIABLES 
- It has values that lie along an evenly dispersed range of numbers when there is absolute zero. It possesses the properties of interval variable and has a clear definition of zero, indication that there is none of that variable.

Examples of which are height, weight, distance, pulse rate and respiratory rate. Most scores stemming from response to survey items are ratio-level values because they typically cannot go below zero.

EXPLANATION: 
- Origin is meaningful number 
- It does not have a true-zero point 
- No negative values   
TYPES OF NUMERICAL VARIABLES

2. DISCRETE VARIABLES 
- This is any variable that has limited number of distinct values and which cannot be divided into fractions like sex, blood group, and number of children in family. 
EXAMPLE: 
1.) Number of registered cards 2.) Number of children in the family 
3.)Population of students 4.) Total number of faculty members.
  
EXPLANATION: 
- Assume any WHOLE VALUE OR NUMBER within the limits of the given variables 
- Variables that are countable and have a finite (having limits) number of possibilities 
- Exact value of variable (have positive value) 
CATEGORICAL VARIABLES

- has values that describe a quality or characteristics of a data or unit 
- Qualitative data in nature 
- It answers the questions WHAT TYPE OR WHICH CATEGORY? 
QUALITATIVE VARIABLES – variables that are not numerical and which values fit into categories. 
TYPES OF CATEGORICAL VARIABLES

A. ORDINAL VARIABLE 
- It represents categories that can be ordered from greatest to smallest. This variable has two or more categories which can be ranked or logically ordered.

Examples of ordinal variable include education level, income brackets/salary scale, levels of satisfaction etc. 
1. Academic Grades - A, B, C 
2. Clothing size - S, M, L, XL, XXL 
3. Measures of attitudes - Strongly agree, agree, disagree, or strongly disagree. 
4. Place in Competition – 1st Runner Up, 2nd Runner Up, 3rd Runner Up, 4th Runner Up 
5. Evaluation – Outstanding, Excellent, Very Good, Average, Fair, Good  
TYPES OF CATEGORICAL VARIABLES

B. NOMINAL VARIABLE 
- It represents categories that cannot be ordered in any particular way. It is a variable with no quantitative value. It has two or more categories but does not imply ordering of cases/not organized. (PURPOSE OF IDENTIFICATION)

EXPLANATION: - No ranking or ordering

Common examples of this variable include eye color, business type, type of learners, political affiliation, basketball fan affiliation, etc. Other examples are; learning styles, language spoken, plate numbers (serve as identification), LRN number, SSS number  
TYPES OF CATEGORICAL VARIABLES

A sub-type of nominal scale with only TWO categories just like sex is known as 
DICHOTOMOUS VARIABLES

Sex (Male and Female) 
Answer (Yes or No) 
Veracity (True or False)

C. POLYCHOTOMOUS VARIABLES These variables that have MANY categories.

1. Educational background (Elementary, High School, College) 
2. Level of performance- excellent, very good, good, satisfactory or poor. 
3. Civil Status – Single, Married, Separated, Widow/Widower 
4. Type of Unicellular Organism – Paramecium, Amoeba, Bacteria, Yeast 
5. Blood type – A+, B+, O+, AB+, A-, B-, O-, AB- 
6. Philippine Ethnic Composition – Tagalog, Bisaya, Cebuano, Bicolano, Hiligaynon, 
Waray-Waray 
7. Religion – Roman Catholic, Muslim, Iglesia ni Cristo, Evangelical, others  
EXPERIMENTAL VARIABLES

 1. INDEPENDENT 
2. DEPENDENT 
3. CONTROL

SHORT RECAP ABOUT EXPERIMENTAL RESEARCH

TREATMENT – Intervention, program, innovation, or strategy 
PRETEST – Assessment before the treatment 
POSTTEST – Assessment after the treatment 
EXPERIMENTAL VARIABLES

1. INDEPENDENT VARIABLES 
 Those that probably cause, influence, or affect outcomes. 
They are invariably called treatment, manipulated, antecedent or predictor variables. This is the cause variable or the one responsible for the conditions that act on something else to bring about changes.

EXPLANATION: - influence or affect another variable - Treatment, innovation, program, or strategy

EXAMPLE: - A study is on the relationship of STUDY HABITS AND ACADEMIC PERFORMANCE OF UTNHS SENIOR HIGH SCHOOL STUDENTS. STUDY HABITS is the independent variable because it influenced the outcome or the performance of the students. 
EXPERIMENTAL VARIABLES

EXPERIMENTAL VARIABLES

2. DEPENDENT VARIABLES 
Those that depend on the independent variables; they are the outcomes or results of the influence of the independent variable. That is why it is also called outcome variable.

EXPLANATION: - The result of the influence of the IV

EXAMPLE: - A study is on the relationship of STUDY HABITS AND ACADEMIC PERFORMANCE OF UTNHS SENIOR HIGH SCHOOL STUDENTS. ACADEMIC PERFORMANCE is the dependent variable because it is depending on the study habits of the students; if the students change their study habit the academic performance also change.

- BY APPLYING THE PREVIOUS EXAMPLE, SKIN MICROBIAL COMMUNITIES IS THE DEPENDENT VARIABLE
EXPERIMENTAL VARIABLES

3. CONTROL VARIABLES 
 A special types of independent variables that are measured in the study because they potentially influence the dependent variable. 
Researchers use statistical procedures (e.g. analysis of covariance) to control these variables.

EXPLANATION: - One which the researcher holds constant – not changing (control) during an experiment. Control group is the one who is exposed in conventional way (considered to be usual or typical – ordinary) 
EXPERIMENTAL VARIABLES

OTHER KINDS OF VARIABLES

INTERVENING VARIABLES that “stand between” the independent and dependent variables, and they show the effects of the independent variable on the dependent variable. 
EXAMPLE: Consider the given below. Even if farm production is good, if the attitude towards payment is negative, loan repayment would be low, whereas, if the attitude towards repayment is positive or favorable, loan repayment would be high.

CONFOUNDING VARIABLES Variables that are not actually measured or observed in a study. They exist but their influence cannot be directly detected in a study. May have operated to explain the relationship between the independent variables and dependent variable, but they were not or could not be easily assessed.
THANK YOU FOR WATCHING! I HOPE YOU'VE ENJOYED LEARNING!

LESSON 6: KINDS, NATURE AND TYPES OF VARIABLES

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