VARIABLES IN
QUANTITATIVE
RESEARCH
LESSON 3
A VARIABLE is anything that has a quantity or
quality that varies.
For instance, during the quarantine period, your
mother planted tomato seedlings in pots. Now
common understanding from science tells you
that several factors are affecting the growth of
tomatoes: sunlight, water, kind of soil, and
nutrients in soil.
The growth of tomatoes and the number of
fruits produced are examples of the
Dependent Variables. The amount of
water, and nutrients in the soil are the
Independent Variables.
The independent variable is also identified
as the presumed cause while the dependent
variable is the presumed effect. In an
experimental quantitative design, the
independent variable is pre-defined and
manipulated by the researcher while the
dependent variable is observed and
measured.
It is important to note other factors that may
influence the outcome (dependent variable)
which are not manipulated or pre-defined by the
researcher. These factors are called Extraneous
Variables. In our example , the presence of pests
and environmental stressors (e.g. pets, extreme
weather) are the extraneous variables.
When the researcher fails to control the
extraneous variable that it caused
considerable effect to the outcome, the
extraneous variable becomes a Confounding
Variable.
VARIABLE
QUANTITATIVE
(Numerical)
QUALITATIVE
(Categorical)
Discrete Continuous Nominal Ordinal
Dichoto
mous
Interval Ratio
Quantitative Variables, also called numerical variables
are the type of variables used in quantitative research
because they are numeric and can be measured. Under
this category are discrete and continuous variables.
Qualitative Variables are also referred to as categorical
variables are not expressed in numbers but are
descriptions or categories. It can be further divided into
nominal, ordinal or dichotomous.
 A discrete variable can assume a countable number of
values or whole numbers. It does not take negative values or
values between fixed points.
o Number of steps to the top of the Eiffel Tower*
 A continuous variable can assume any value along a given
interval of a number line. It takes fractional (non-whole
number) values that can either be a positive or a negative.
o The time a tourist stays at the top
once s/he gets there
 Discrete variables
o Number of sales
o Number of calls
o Shares of stock
o People in line
o Mistakes per page
 Continuous variables
o Length
o Depth
o Volume
o Time
o Weight
Levels of
Measurement
It was the American psychologist Stanley Smith
Stevens who proposed the levels of measurement
or scales of measure.
Nominal Level
 Data in this level are classified into categories. Names are
used as labels. Numbers and letters are used to represent
variables.
Examples:
a. Marital Status: Single, Married, Divorce
b. Sex: Male, Female
1. M maybe used instead of Male
F maybe used instead of Female
2. 1 maybe used instead of Male
2 maybe used instead of Female
Ordinal Level
 Data in this level are ranked but the degree of difference
between them are not determined. Items are ordered when
sorted out.
Example:
a. Size – small, medium, large, extra large
b. Rank – 1st, 2nd, 3rd, etc.
Interval Level
 The degree of difference between the data can be
specified but not the ratio between them. In this
level, zero (0) does not mean total absence of what
being measured.
Example:
a. Temperature in Celsius Scale
Ratio Level
 In this level, data such as scores can be expressed as ratio.
In ratio level, zero (0) has no actual or true value. Most
measurement in engineering and physical sciences are in
ratio level.
Examples:
a. Mass is measured on ratio scale.
b. Length is also measured on ratio scale.
Dichotomous
Dichotomous are consisting of only two
distinct categories or values.
For example, a response to a question either
be a yes or no.
B. Tell what kind of measurement scale is
appropriate for the following information.
Nominal – Ordinal – Interval – Ratio - Dichotomous
1) Eye color
2) Gender
3) Race
4) Religious affiliation
5) Weights of basketball
players
6) Temperature
7) Speed of sound
8) Top ten in the nursing board
examination
9) Height
10)Sizes of shoes

PR2-Module-1-Lesson-3.pptx

  • 1.
  • 2.
    A VARIABLE isanything that has a quantity or quality that varies. For instance, during the quarantine period, your mother planted tomato seedlings in pots. Now common understanding from science tells you that several factors are affecting the growth of tomatoes: sunlight, water, kind of soil, and nutrients in soil.
  • 3.
    The growth oftomatoes and the number of fruits produced are examples of the Dependent Variables. The amount of water, and nutrients in the soil are the Independent Variables.
  • 4.
    The independent variableis also identified as the presumed cause while the dependent variable is the presumed effect. In an experimental quantitative design, the independent variable is pre-defined and manipulated by the researcher while the dependent variable is observed and measured.
  • 5.
    It is importantto note other factors that may influence the outcome (dependent variable) which are not manipulated or pre-defined by the researcher. These factors are called Extraneous Variables. In our example , the presence of pests and environmental stressors (e.g. pets, extreme weather) are the extraneous variables.
  • 6.
    When the researcherfails to control the extraneous variable that it caused considerable effect to the outcome, the extraneous variable becomes a Confounding Variable.
  • 7.
  • 8.
    Quantitative Variables, alsocalled numerical variables are the type of variables used in quantitative research because they are numeric and can be measured. Under this category are discrete and continuous variables. Qualitative Variables are also referred to as categorical variables are not expressed in numbers but are descriptions or categories. It can be further divided into nominal, ordinal or dichotomous.
  • 9.
     A discretevariable can assume a countable number of values or whole numbers. It does not take negative values or values between fixed points. o Number of steps to the top of the Eiffel Tower*  A continuous variable can assume any value along a given interval of a number line. It takes fractional (non-whole number) values that can either be a positive or a negative. o The time a tourist stays at the top once s/he gets there
  • 10.
     Discrete variables oNumber of sales o Number of calls o Shares of stock o People in line o Mistakes per page  Continuous variables o Length o Depth o Volume o Time o Weight
  • 11.
    Levels of Measurement It wasthe American psychologist Stanley Smith Stevens who proposed the levels of measurement or scales of measure.
  • 12.
    Nominal Level  Datain this level are classified into categories. Names are used as labels. Numbers and letters are used to represent variables. Examples: a. Marital Status: Single, Married, Divorce b. Sex: Male, Female 1. M maybe used instead of Male F maybe used instead of Female 2. 1 maybe used instead of Male 2 maybe used instead of Female
  • 13.
    Ordinal Level  Datain this level are ranked but the degree of difference between them are not determined. Items are ordered when sorted out. Example: a. Size – small, medium, large, extra large b. Rank – 1st, 2nd, 3rd, etc.
  • 14.
    Interval Level  Thedegree of difference between the data can be specified but not the ratio between them. In this level, zero (0) does not mean total absence of what being measured. Example: a. Temperature in Celsius Scale
  • 15.
    Ratio Level  Inthis level, data such as scores can be expressed as ratio. In ratio level, zero (0) has no actual or true value. Most measurement in engineering and physical sciences are in ratio level. Examples: a. Mass is measured on ratio scale. b. Length is also measured on ratio scale.
  • 16.
    Dichotomous Dichotomous are consistingof only two distinct categories or values. For example, a response to a question either be a yes or no.
  • 19.
    B. Tell whatkind of measurement scale is appropriate for the following information. Nominal – Ordinal – Interval – Ratio - Dichotomous 1) Eye color 2) Gender 3) Race 4) Religious affiliation 5) Weights of basketball players 6) Temperature 7) Speed of sound 8) Top ten in the nursing board examination 9) Height 10)Sizes of shoes