Types of variables in research
- 1. TypesofVariablesinResearch Dr. Ruchi jain Associate professor Department of Commerce-Financial Studies Iis (deemed to be university) Jaipur
- 2. INTRODUCTION • Each person/thing we collect data on is called an observation (in our research work these are usually people/subjects). • Observation (participants) possess a variety of characteristics. • If a characteristic of an observation (participant) is the same for every member of the group i.e. it does not vary, it is called aconstant • If a characteristic of an observation (participant) differs for group members it is calledavariable.
- 3. MEANING OFVARIABLES • A variable is a concept or abstract idea that can be described in measurable terms. In research, this term refers to the measurable characteristics, qualities, traits, or attributes of a particular individual, object, or situation being studied. • Anything that can vary can be considered a variable. For instance, age can be considered a variable because age can take different values for different people or for the same person at different times. Similarly, Income can be considered a variable because a person's Income canbe assignedavalue.
- 4. • Variables are properties or characteristics of some event, object, or person that can take on different values or amounts. measure, but also something that we • A variable is not only something that we can manipulate and something we cancontrol for.
- 6. Dependent andIndependent Variables • Independent variables are variables which are manipulated or controlled or changed. It is what the researcher studies to seeits relationship or effects. Presumed or possiblecause • Dependent variables are the outcome variables and are the variables for which we calculate statistics. The variable which changes on account of independent variable is known as influenced or affected by thedependent variable. i.e.It is independent variable Presumed results(Effect)
- 8. Example • Imagine that a tutor asks 100 students to complete a maths test. The tutor wants to know why some students perform better than others. Whilst the tutor does not know the answer to this, she thinks that it might be because of two reasons: (1) some students spend more time revising for their test; and (2) some students are naturally more intelligent than others. As such, the tutor decides to investigate the effect of revision time and intelligence on the test performance of the 100 students. What are the dependent and independent variables for thestudy ?
- 9. Solution • DependentVariable:TestMark (measured from 0to100) • Independent Variables: Revision time (measured in hours) Intelligence (measured usingIQscore)
- 10. Activity • Indentify the dependent andIndependent Variables for the followingexamples: 1.Astudy of teacher-student classroom interaction at different levels ofschooling. 2.Acomparative study of the professional attitudes of secondary school teachersby gender.
- 11. Solution 1.Independent variable: Levelof schooling, four categories – primary, upper primary,secondary and junior college. Dependent variable: Scoreon aclassroom observation inventory, which measures teacher– student interaction 2.Independent variable: Gender of the teacher– male, female. Dependent variable: Scoreon aprofessional attitude inventory.
- 12. Moderator VariableModerator Variable • It is aspecial type of independentvariable. • The independent variable’s relationship with the dependent variable may change under different conditions. That condition is the moderator variable. • That factor which is measured, manipulated, or selected by the experimenter to discover whether it modifies the relationship of the independent variable to an observed phenomenon.
- 13. Example • Astrong relationship has been observed between the quality of library facilities (X) and the performance of the students (Y). Although this relationship is supposed to be true generally, it is nevertheless contingent on the interest and inclination of the students. It means that only those students who have the interest and inclination to use the library will show improved performance in their studies. • In this relationship interest and inclination is moderating variable i.e. which moderates the strength of the association between X and Y variables
- 14. Quantitative andQualitativeVariables • Qualitative variables do not express differences in amount, onlydifferences. • They are sometimes referred to as categorical variables because they classify by categories. Ordinal, Nominal variables are qualititative • Nominal variables such as gender, religion, or eye color are categorical variables. Generally speaking, categorical variables
- 17. NominalScaleNominal scale • Nominal Scale,also called the categorical variable scale, is defined asascaleused for labeling variables into distinct classifications and doesn’t involve aquantitative value or order. • This scaleis the simplest of the fourvariable measurement scales.
- 18. Nominal ScaleExamples • Gender • Political preferences • Placeof residence What is yourGender What is yourPolitical preference? Where do youlive? M- Male F-Female 1 Independent 2 Democrat 3 Republican 1 Suburbs 2 City 3 Town
- 19. OrdinalScaleOrdinal Scale • Ordinal Scale is defined as a variable measurement scale used to simply depict the order of variables(what’s important and significant) and not the difference between each of the variables(differences between each one is not reallyknown) • For example, is the difference between “OK” and “Unhappy” the same as the difference between “Very Happy” and “Happy?” Wecan’tsay.
- 20. • Ordinal scales are typically measures of non- numeric concepts like satisfaction, happiness, discomfort, etc. • “Ordinal” is easy to remember because is sounds like “order” and that’s the key to remember with “ordinal scales”–it is the order thatmatters. • Example: On a survey you might code Educational Attainment as 0=less than high school; 1=some high school.; 2=high school degree; 3=some college; 4=college degree; 5=post college. In this measure, higher numbers mean more education. But is distance from 0 to 1 sameas3 to 4?Of coursenot.
- 21. Intervalscale • Interval Scale is defined as a numerical scale where the order of the variables is known as well as the difference between these variables. Variables which have familiar, constant and computable differences are classified using the Interval scale. • Interval scale contains all the properties of ordinal scale, in addition to which, it offers a calculation of the difference between variables. The main characteristic of this scale is the equidistant difference betweenobjects.
- 22. • In statistics, interval scaleis frequently usedas anumerical value cannot only be assignedto variables but calculation on the basis of those values canalso be carried out. • Calendar yearsand time also fall underthis category of measurementscales. • Likert scaleis the most-used intervalscale examples.
- 23. RatioScaleRatio scale • Ratio Scale is defined as a variable measurement scale that not only produces the order of variables but also makes the difference between variables known along with information on the value of true zero. • It is calculated by assuming that the variables have an option for zero, the difference between the two variables is the same and there is aspecific order between theoptions.
- 24. • In addition to the fact that the ratio scale does everything that a nominal, ordinal and interval scale can do, it can also establish the value of absolutezero. • Examples Thefollowing questions fall under the Ratio Scalecategory: • What is your daughter’s current height? – Lessthan 5feet. – 5 feet 1 inch – 5 feet 5inches – 5 feet 6 inches- 6 feet – More than 6feet • What is your weight inkilograms? – Lessthan 50kilograms – 51- 70kilograms – 71- 90kilograms – 91-110 kilograms – More than 110kilograms
- 25. Continuous andDiscontinuous Variables • If the values of a variable can be divided into fractions then we call itacontinuous variable. • Such a variable can take infinite number of values. Income, temperature, age, or a test score are examplesof continuousvariables. • These variables may take on values within a given range or, in some cases,an infinite set.
- 26. • Any variable that has a limited number of distinct values and which cannot be divided into fractions, is adiscontinuous variable. • Such a variable is also called as categorical variable or classificatory variable, or discrete variable. • Some variables have only two values, reflecting the presence or absence of a property: employed-unemployed or male-female have two values. These variables are referred to as dichotomous. • There are others that can take added categories such as the demographic variables of race, religion. All such variables that produce data that fit into categories are said to be onlydiscrete/categorical/classificatory, since certain values arepossible.
- 27. VARIABLESEXAMPLES Examples Dichotomous •Gender:Male and female •Variables Typeof property:Commercial and residential •Pregnant and non pregnant •Alive and dead •HIVpositive and HIVnegative •Education: Literate andilliterate Trichotomous •Residence:Urban, semi urban andrural Variables •Religion: Hindu, muslim,and Christianity. Multiple Variables •Blood groups:A,B,ABand O
- 28. DEMOGRAPHIC VARIABLES: • “Demographic variables are characteristics or attributes of subjects that are collected to describe the sample”. They are also called sample characteristics. • It means these variables describe study sample and determine if samples are representative of the population ofinterest. • Although demographic variables cannot be manipulated, researchers can explain relationships between demographic variables and d e p e n d e nt v ar i ab l e s. • Some common demographic variables are age, gender, occupation, marital status, incomeetc.
- 29. ExtraneousvariableExtraneous Variable • It happens sometimes that after completion of the study we wonder that the actual result is not what we expected. In spite of taking all the possible measures the outcome is unexpected. It is becauseof extraneousvariables • Variables that may affect research outcomes but have not been adequately considered in the study are termed as extraneous variables. Extraneous variables exist in all studies and can affect the measurement of study variables and the relationship among thesevariables.
- 30. • Extraneous variables that are not recognized until the study is in process, or are recognized before the study is initiated but cannot be controlled, are referred to as confounding variables. These variables interferes the results of the existingactivity. • Certain external variables may influence the relationship between the research variables, even though researcher cannot see it. These variables are called interveningvariables.
- 31. ControlVariable • Sometimes certain characteristics of the objects under scrutiny are deliberately left unchanged. These are known asconstant or controlled variables. • The variables that are not measured in a particular study must be held constant, neutralized/balanced, or eliminated, so they will not have a biasing effect on the other variables. • In the ice cube experiment, one constant or controllable variable could be the size and shape of the cube. By keeping the ice cubes' sizes and shapes the same, it's easier to measure the differences between the cubes as they melt after shifting their positions, as they all started out as the same size.