Different Variables in Quantitative Research~GM Lectures
Summary
TLDRThis 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
- π Variables are factors that can change or affect the results of a study and are crucial for understanding differences in research.
- π 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).
- π· 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).
- π§ Experimental variables are used to determine causal relationships and include independent variables, dependent variables, control variables, moderating variables, and extraneous variables.
- βοΈ Independent variables are manipulated to observe their effect on dependent variables, which are the outcomes being measured.
- π Control variables are held constant to isolate the effects of independent variables on dependent variables.
- π Moderator variables influence how the relationship between independent and dependent variables changes under different conditions.
- π Extraneous variables are existing variables that can influence study outcomes and should be controlled to avoid confounding results.
- π Non-experimental variables are not manipulated by researchers and include predictor variables, which affect criterion variables in non-experimental studies.
- π‘ 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 studyβs results. Itβs 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
π 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.
π’ 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.
π·οΈ 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.
π¬ 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.
π 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.
Mindmap
Keywords
π‘Variables
π‘Numeric Variables
π‘Continuous or Interval Variables
π‘Discrete Variables
π‘Categorical Variables
π‘Ordinal Variables
π‘Nominal Variables
π‘Experimental Variables
π‘Independent Variables
π‘Dependent Variables
π‘Control Variables
π‘Moderator Variables
π‘Extraneous Variables
π‘Non-Experimental Variables
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 wholeζ°εΌ 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
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