Different Variables in Quantitative Research~GM Lectures

Summary

This lecture delves into the concept of variables in research, explaining how they can influence outcomes. It distinguishes between numeric and categorical variables, with the former including continuous, interval, and discrete types, and the latter encompassing ordinal, nominal, dichotomous, and polytomous categories. The lecture further explores experimental variables, detailing independent and dependent variables, and the roles of control, moderating, and extraneous variables. It concludes by emphasizing the importance of understanding variable classifications for meaningful research analysis.

Takeaways

• 🔍 Variables are factors that can change or affect the results of a study and are crucial for understanding differences in research.
• 📊 Numeric variables describe measurable quantities and can be either continuous (e.g., time, age, weight, height) or discrete (e.g., class attendance, number of establishments, number of children in a family).
• 🏷 Categorical variables describe qualities or characteristics and include ordinal (e.g., clothing size, academic ranking), nominal (e.g., learning styles, blood type, language spoken), dichotomous (e.g., yes/no, true/false, gender), and polytomous variables (e.g., performance level, educational attainment).
• 🔧 Experimental variables are used to determine causal relationships and include independent variables, dependent variables, control variables, moderating variables, and extraneous variables.
• ⚖️ Independent variables are manipulated to observe their effect on dependent variables, which are the outcomes being measured.
• 🎚 Control variables are held constant to isolate the effects of independent variables on dependent variables.
• 🔄 Moderator variables influence how the relationship between independent and dependent variables changes under different conditions.
• 🌐 Extraneous variables are existing variables that can influence study outcomes and should be controlled to avoid confounding results.
• 📈 Non-experimental variables are not manipulated by researchers and include predictor variables, which affect criterion variables in non-experimental studies.
• 💡 Recognizing and classifying variables is essential for researchers to understand how they interact and affect each other, leading to more meaningful study outcomes.

Q & A

What is a variable in the context of research?

A variable is an entity that can take on different values. It represents an aspect of a theory that can change or vary and can affect the results of a study.

What are some examples of variables mentioned in the script?

Examples of variables include age, gender, IQ level, lifestyle, temperature, and medical treatment used.

What is the difference between continuous and discrete variables?

Continuous variables can assume any value between certain real numbers and include finer measurements like time, weight, or height. Discrete variables only take whole numbers, such as the number of children in a family or class attendance.

How are categorical variables classified?

Categorical variables are qualitative and are divided into ordinal, nominal, dichotomous, and polycautious variables.

What distinguishes ordinal variables from nominal variables?

Ordinal variables can be logically ordered or ranked (e.g., clothing size, academic ranking), while nominal variables cannot be logically ordered and are used for classification or identification (e.g., blood type, plate numbers).

What is a dichotomous variable, and how does it differ from a polycautious variable?

A dichotomous variable represents only two categories (e.g., yes/no, true/false), while a polycautious variable has many possible categories (e.g., educational attainment, performance level).

What is the role of independent and dependent variables in experimental research?

Independent variables are presumed to cause changes in another variable and are manipulated during experiments. Dependent variables change as a result of the independent variable's manipulation.

What is the function of control and moderator variables in an experiment?

Control variables are held constant to help identify differences in outcomes, while moderator variables delineate how relationships change under different conditions or circumstances.

What are extraneous variables, and why is it important to control them?

Extraneous variables are variables that already exist during an experiment and can influence the study’s results. It’s important to control them because they might cause alternative results not related to the variables being studied.

How do non-experimental variables differ from experimental variables?

Non-experimental variables cannot be manipulated by the researcher and are used in non-experimental studies. They include predictor variables, which affect other variables, and criterion variables, which are influenced by predictor variables.

Outlines

00:00

📚 Introduction to Variables

This paragraph introduces the concept of variables within the context of a study on low academic performance. Variables are defined as entities that can take on different values and can influence the results of a study. Examples such as understanding instructions, studying habits, time management, and focus during review are given as potential variables. The paragraph also explains that variables can be of various types, including age, gender, IQ level, lifestyle, temperature, or medical treatments, emphasizing that any factor a researcher is interested in can be considered a variable.

05:00

🔢 Numeric Variables

This section delves into numeric variables, which are quantitative and can describe a measurable numerical quantity. It distinguishes between continuous or interval variables and discrete variables. Continuous or interval variables can take any value within a range (e.g., time, age, weight, height), while discrete variables are whole numbers only (e.g., class attendance, number of establishments, children in a family). The purpose of numeric variables is to quantify data and provide measurable insights.

10:01

🏷️ Categorical Variables

Categorical variables are qualitative and describe qualities or characteristics. They are divided into ordinal, nominal, dichotomous, and polycautious variables. Ordinal variables can be logically ordered (e.g., clothing size, academic ranking, satisfaction levels). Nominal variables are for identification and do not have a logical order (e.g., learning styles, language spoken, blood type). Dichotomous variables have two categories (e.g., yes/no, true/false, gender), and polycautious variables have multiple categories (e.g., performance level, educational attainment). These variables help classify and categorize data.

15:02

🔬 Experimental Variables

The paragraph discusses experimental variables that establish causal relationships. It includes independent variables, which are manipulated to cause changes, and dependent variables, which change as a result. The example of studying affecting academic performance is used to illustrate this relationship. Control variables are mentioned as constants that help isolate the effect of independent variables, while moderator variables influence how relationships change under different conditions. Extraneous variables are also discussed as existing factors that can affect outcomes and need to be controlled to ensure the validity of the study.

📈 Non-Experimental Variables

This final paragraph covers non-experimental variables, which cannot be manipulated by researchers and are used in non-experimental studies. Predictor variables are those that can affect other variables, while criterion variables are influenced by predictor variables. Examples given include management styles affecting employee satisfaction and guidance counseling programs influencing absenteeism and dropout rates. The paragraph concludes by emphasizing the importance of understanding variables and their classifications for meaningful research outcomes.

Keywords

💡Variables

Variables are entities that can take on different values and are fundamental to understanding differences in research studies. In the video, variables are used to identify factors that could influence low academic performance, such as not understanding instructions, sleeping instead of studying, running out of time, or lack of focus. The concept is central to the theme as it helps researchers to isolate and study the factors that may affect outcomes.

💡Numeric Variables

Numeric variables describe measurable quantities and are quantitative in nature. They are further divided into continuous or interval variables and discrete variables. In the script, examples include time, age, weight, and height, which can take any value within a range, illustrating how numeric variables are used to quantify aspects of a study.

💡Continuous or Interval Variables

Continuous or interval variables can assume any value within a set of real numbers, reflecting a spectrum of possible values. The video uses time, age, and height as examples, showing that these variables can have fractional or decimal values, which is crucial for understanding the nuances in data measurement.

💡Discrete Variables

Discrete variables can only take whole数值 values within given limits, such as class attendance or the number of children in a family. The video emphasizes that these variables are distinct from continuous ones because they do not recognize values between whole numbers, which is important for categorizing data that cannot be divided into smaller units.

💡Categorical Variables

Categorical variables describe qualities or characteristics and are qualitative in nature. They are divided into ordinal, nominal, dichotomous, and polycautimus variables. The video explains that these variables answer questions about type or category, which is essential for classifying data in non-numeric ways.

💡Ordinal Variables

Ordinal variables can be logically ordered or ranked, such as clothing sizes, academic rankings, or levels of satisfaction. The video uses these examples to demonstrate how ordinal variables allow for a ranking system within categorical data, which is useful for comparing relative standings or preferences.

💡Nominal Variables

Nominal variables are used for identification and classification without any logical order, like blood types or languages spoken. The video clarifies that nominal variables are not ranked; they simply categorize data, which is important for understanding distinct groups or classifications within a study.

💡Experimental Variables

Experimental variables are used to determine causal relationships and include independent, dependent, control, moderating, and extraneous variables. The video discusses how these variables are manipulated or observed to understand their effects on outcomes, which is central to experimental research design.

💡Independent Variables

Independent variables are presumed to cause changes in another variable and are manipulated in an experiment. The video gives the example of studying affecting academic performance, illustrating how independent variables are the potential causes in a study.

💡Dependent Variables

Dependent variables change due to the manipulation of an independent variable and are monitored in an experiment. The video explains that academic performance is a dependent variable because it changes based on the independent variable of studying, highlighting the effect being measured.

💡Control Variables

Control variables are held constant in an experiment to isolate the effects of the independent variable. The video uses class duration as an example, showing how control variables help ensure that observed effects are due to the independent variable and not confounded by other factors.

💡Moderator Variables

Moderator variables influence how the relationship between other variables changes under different conditions. The video discusses how the genre of music played could moderate the effect of music on academic performance, indicating how moderator variables can alter the strength or direction of relationships.

💡Extraneous Variables

Extraneous variables are existing variables that could influence the results of a study and must be controlled to avoid confounding the outcomes. The video mentions noise, ventilation, and lighting as examples, emphasizing the need to control for these variables to ensure the study's validity.

💡Non-Experimental Variables

Non-experimental variables cannot be manipulated by the researcher and are used in non-experimental studies. The video differentiates between predictor and criterion variables, explaining how predictor variables like management styles can affect criterion variables like employee satisfaction, which is crucial for understanding relationships without experimental manipulation.

Highlights

Variables are factors that can influence the results of a study.

A variable is an entity that can take on different values and is central to understanding differences in research studies.

Variables can be numeric, categorical, experimental, or non-experimental, each serving different roles in a study.

Numeric variables describe measurable quantities and can be either continuous or discrete.

Continuous variables can take any value within a range, such as time measured in hours, minutes, and seconds.

Discrete variables only take whole数值 values, like the number of children in a family.

Categorical variables describe qualities or characteristics and are qualitative in nature.

Ordinal variables can be logically ordered or ranked, such as clothing sizes or academic rankings.

Nominal variables are used for identification and do not have a logical order, like blood types or languages spoken.

Dichotomous variables represent two categories, such as gender or true/false answers.

Polytomous variables have multiple categories, like different levels of education or performance levels.

Experimental variables determine causal relationships and include independent, dependent, control, moderating, and extraneous variables.

Independent variables are manipulated to observe their effect on dependent variables.

Control variables are held constant to isolate the effects of independent variables.

Moderator variables influence how the relationship between independent and dependent variables changes under different conditions.

Extraneous variables are external factors that can affect the outcome of a study and should be controlled.

Non-experimental variables are not manipulated by researchers and include predictor and criterion variables.

Understanding variable classifications is crucial for meaningful research discussions and outcomes.

Transcripts

good day everyone for this particular

lecture we will be discussing about the

different types of variables

but first let's analyze this situation

here

say for example a teacher wants to

identify the factors that influence the

low academic performance of students

what are some possible factors it may be

that the student was not able to

understand the instruction

or instead of studying the student

simply slept

or perhaps the student ran out of time

and was in a hurry to finish the test or

even

during the review the student was not

able to focus

all these factors being confused

sleeping instead of reviewing running

out of time

and being out of focus can be considered

as

variables that contribute to our study

[Music]

now at this point let us talk about the

definition of a variable

a variable is an entity that can take on

different values

it is an aspect of a theory that can

vary or change

as part of the interaction within the

theory

or anything that can change or affect

the results of a particular study

take note that anything that can vary

can be considered a variable

these are needed to understand

differences in a particular research

study

[Music]

again a variable may take different

forms

it can be age gender

iq level the lifestyle of an individual

temperature or medical treatment used

remember that anything can be a variable

as long as it is something that a

researcher is interested in

now at this point let's talk about the

different classifications of variables

variables may be classified as numeric

categorical experimental

or non-experimental the classifications

would determine the roles of variables

in a particular study

now let's talk about the numeric

variable classification

the numeric classification of variables

are variables with values that describe

a measurable numerical quantity

pretty much it answers the questions how

many

or how much meaning to say that numeric

variables

are considered quantitative data numeric

variables are further divided into two

types which are

continuous or interval variables and

discrete variables

continuous or interval variables assume

any value between a certain set of real

numbers

depending on the scale used while

discrete

variables can only assume any whole

value

within the limits of the given variables

now some of the examples of the

continuous or interval variables can be

time if you're going to observe in time

we do not only look at the hours

we also recognize the existence of

minutes

and seconds age could also be an example

because in between the age of 10 and 11

we recognize that there are people who

are ten and a half

and even ten and three quarters weight

is also an example

because we do not only focus on whole

numbers for the weight

we also have grams and milligrams in

between

and finally another example of

a continuous variable could be the

height

when we recognize or when we indicate

the height of a person we do not only

look at the feet

we also consider the centimeters and

inches

take note that continuous or interval

variables in the simplest description

recognize the value between whole

numbers

now let's proceed with the discussion of

discrete variables

discrete variables unlike the continuous

or

interval variables that recognize the

existence of values in between whole

numbers

only focus on the whole numbers itself

some examples would be class attendance

number of establishments in an area

and number of children in the family

again

note that discrete variables are whole

numbers because

remember in class attendance we do not

have half a student

as well as in the number of the children

in the family we don't have two and a

half children in the family

it always recognizes that values are

that of a whole number

the next variable classification is the

categorical variable

categorical variables are variables with

values that describe a quality

or characteristic of a data unit pretty

much it answers the questions

what type or which category

hence we have the term categorical now

unlike the numeric variables

categorical variables are qualitative in

nature

and are further divided into four types

which

are ordinal variables nominal variables

dichotomous variables and polycautimus

variables

[Music]

let's first talk about the ordinal

variables

ordinal variables can take a value which

can be logically ordered or

ranked some examples would be clothing

size

academic ranking levels of satisfaction

and salary scale take note of the

operative terms

which are values that can be logically

ordered

and ranked some of these examples would

explain that

a person who is size x s or extra small

is ranked differently than that of

someone who is

a smaller size take note that it

gradually gets

bigger in terms of the ranking

similarly in terms of academic ranking a

person who ranks first

is different than someone who ranks

second

and someone ranks third in terms of

levels of satisfaction

of course a person who is very satisfied

has a different level compared to

someone who is simply satisfied

or someone who is actually very

dissatisfied

in the simplest terms ordinal variables

serve the purpose of

classification and ranking

now let's proceed to nominal variables

nominal variables unlike ordinal

variables wherein the values can be

arranged logically in terms of ranking

have values which cannot be organized in

a logical sequence

some examples would be the learning

styles

the language spoken blood type

and plate numbers now you might be

thinking

plate numbers have numbers in them

aren't they supposed to be

numeric variable or ordinal variables

well the answer is no

because plate numbers serve the purpose

of nominal variables which

is for the purpose of identification

remember that plate numbers

are unique in order to identify the

vehicle that it is assigned to

similar to your blood type blood type a

is different from blood type b however

having blood type a doesn't mean you're

greater than persons who have blood type

b

or having a blood type a b doesn't mean

you're the greatest among all these

blood types

in terms of learning styles being a

visual learner doesn't mean you're

greater than

someone who is musical or auditory

learner

it simply is for the purpose of

identifying which particular learning

purpose or learning style would serve

you best

in terms of the language spoken learning

or speaking one particular language

doesn't mean you're greater than all the

others

it simply is for the purpose of

identifying in which country you came

from

whether from your japan from china

from korea or from thailand however

it doesn't mean that if you speak thai

it doesn't mean that you're greater than

those who speak korean

or even the others again it's merely for

the purpose of

identification

before we proceed let's sum up the

differences in similarities between

ordinal variables and nominal variables

ordinal variables and nominal variables

are both categorical

however ordinal variables can be

organized

or ranked while nominal variables would

be for classification and identification

purposes only

let's now proceed with the other

categorical variable classifications

which are dichotomous variables

and polycautious variables

dichotomous variables are variables that

represent only two categories example

would be a yes or no choice true or

false or even

gender in terms of biological gender

whereas polycartomas variables are

variables that have many possible

categories

example would be performance level

and educational attainment

take note of the operative terms between

the two

decatus variables would only have two

categories

while polycontinuous variables would

have many possible categories

[Music]

now let's talk about another variable

classification which

is experimental variable experimental

variable

are variables that determine causal

relationships

it is subdivided into independent

variables

dependent variables control variables

moderating variables and extraneous

variables

now let's talk about independent

variables and dependent variables

independent variables are presumed to

cause

changes in another variable these are

usually manipulated in an experiment

hence independent variables are also

called as the causal variable

while dependent variables are variables

that change

because of another variable these are

usually affected by the manipulation of

the independent variable

and dependent variables are the

variables that are monitored

in an experiment hence we call dependent

variables as the effect

variable

[Music]

let's take for example this particular

study on the effect of studying in the

academic performance of students

so we have the two variables which are

studying

an academic performance from this

particular situation we could determine

that studying is the independent

variable

and academic performance is the

dependent variable

because studying greatly affects

academic performance

in another example we have the effect of

diet and exercise on the physical

fitness of individuals

similarly we have two variables which

are diet and exercise

and physical fitness from this

particular situation we could determine

that diet and exercise

is a dependent variable while physical

fitness

is the dependent variable because diet

and exercise

affects the physical fitness of

individuals

[Music]

at this point we now focus on control

variables and moderator variables

control variables are variables that are

held constant

these help to identify the possible

differences

in the outcomes as a result of

controlling certain variables

while moderator variables are variables

that delineates how a relationship of

interest changes

under different conditions or

circumstances

moderator variables may be quantitative

or qualitative in nature

[Music]

let's look at this example on the study

regarding the effect

of playing music on the academic

performance of students

we have our students here playing music

and academic performance from this

particular situation we are able to

identify that playing music is our

independent variable

as it might influence the academic

performance of our students

a possible moderator variable would be

the genre of music that is played

remember that a moderator variable

introduces

change in the results if done in a

different situation or

condition as such we try to identify

which particular genre of music whether

classical music

or rock music would be effective in

terms of improving the academic rate of

the students

now a possible control variable would be

the class duration which is 60 minutes

per class

regardless whether you're a class

exposed to classical music or the class

exposed to rock music

both groups will have the same duration

of class in order to determine

the possible effects of music exposure

to the students

and lastly we have extraneous variables

extraneous variables are variables that

are already existing during the

conduct of an experiment these variables

could influence the results of the study

as such as much as possible must be

controlled because they can

offer an alternative result take note

that these are variables which are

already existing or extra variables that

are already existing hence we have the

term extraneous variables

[Music]

let's go back to our example earlier on

the study regarding the effect of

playing music on the academic

performance of students

we have playing music as our independent

variable

and academic performance as our

dependent variable

a possible extraneous variable that

might influence or change the result

would be noise another would be

ventilation

and lighting noise of course would cause

a distraction to the students

hence they would not be able to focus

properly even if they are exposed to

classical music

or rock music whereas

ventilation and lighting might result to

a change in the atmosphere

which would result to the students

feeling uncomfortable

in terms of studying in that particular

area

regardless whether they're exposed to

classical music

or rock music in both situations

noise and ventilation and lighting are

considered extraneous variables

because if they are not controlled they

might offer a different result

that is not expected in the study itself

and the last variable classification

would be the non-experimental variables

non-experimental variables are variables

which cannot be manipulated by the

researcher

hence it is for non-experimental studies

non-experimental variables are further

classified into predictor variables

which are variables that can change or

affect other variables in a

non-experimental study

and criterion variables which are

variables that are influenced by the

predictor variable

in a non-experimental study

let's consider these examples here on

the influence of management styles on

employee satisfaction

our predictor variable would be the

management styles

because it affects the criterion

variable

which is the employee satisfaction

in another example we have the conduct

of guidance counseling programs and

degree of absenteeism and dropout rate

among

grade 8 students our predictor variable

would be the conduct of guidance

counseling programs

as it might influence or affect our

criterion variable which is

the degree of absenteeism and dropout

rate

as we end our discussion let's focus on

this particular reflection

recognizing variables and knowing their

classification and roles would help

researchers have a more detailed idea

regarding how the variables in their

study interact and affect each other

in turn this contributes to a more

meaningful discussion regarding the

possible outcomes of a study

as reflected in their identified

[Music]

variables