THE STATISTICAL PROCESS OF HOW TO DESCRIBE STATISTICAL VARIABLES

OR DATA

HOW TO DESCRIBE STATISTICAL VARIABLES OR DATA?

Determine the appropriate statistical tools to be used in processing and in analyzing

data for research;

Will give an idea for researchers on how to construct a research paradigm;

Will guide the researcher in studying problems and hypothesis in their research.

A need to study the uses, the measures, and the classification of variables.

WHAT IS MEASUREMENT?

- Refers to the assignment of numbers to observation made of objects or persons in

such a way that the numbers can be subjected to statistical analysis by manipulating

or using the needed operations according to mathematical rules of correspondence.

These rules prescribe or give the mathematical formula on how correspondence

between sets of data are to be calculated for purposes of statistical analysis.

2 TYPES OF STATISCAL DATA:

1. Numerical Data – are expressed in numerical values such in natural and rational numbers.

It can be either discrete or continuous data.

Continuous data – are expressed in whole numbers, decimals or fractions.

2. Categorical data – are classificatory data and are not expressed in numerical values.

-Merely labeled and classified into categories.

WHAT DO THE TERM VARIABLE MEAN?

- Refers to a factor, property, attribute, characteristics or behavior whereby the members of

the group or set vary or differ from one another. For instance, the members of the group

may vary in sex, eye color, intelligence, attitude, socioeconomic status, teacher behavior,

academic performance, job satisfaction, managerial style, value orientation and others.

That is why, variables are used and studied in research.

However, the word constant is not a variable when referring to a property whereby the

members of the group do not differ from one another. Say for example, when you deal

with only one level of socioeconomic status, low socioeconomic status is constant, not a

variable. Because a variable is a simply anything that can vary.

CLASSICATION OF VARIABLES ACCORDING TO FUNCTIONAL

RELATIONSHIPS

Variables are classified into independent and dependent with respect to their functional

relationship for example, if you treat variable y as a function of variable Z, then Z is your

independent variables and Y is your dependent on the value of Z, say mental ability. To further

illustrate functional relationship among variables, let Y = f(X), Y as a function of X; such that if

Y = 3x + 1;

If x = 0; y = 1

x = 1; y = 4

x = 2; y = 7

x = 3; y = 10

X 0 1 2 3 - 1 -2 -3Y = f (x) 0 4 7 10 -2 -5 -8

If x = -1; y = -2

x = -2; y = -5

x = -3; y = -8

This means that the value of y simply depends on the value of x. we can identify from

functions that x is an independent variable, while y is a dependent variable. If for example one of

the variables for investigation is mathematics performance of the students and the other variable

is methods of teaching mathematics, by using the concept according to its functional relations,

the mathematics performance of the students is dependent on the methods used by the teacher in

teaching mathematics. Hence, we can say that mathematics performance is the dependent

variable while methods of teaching are independent variable.

Classifying Variables according to Functional Relations Have different Purposes or Roles

Independent Variables

- refers to the factor, property, attribute, characteristics or approach that

is introduced, manipulated, or treated to determine if it influences or

causes a change on the dependent variable.

- Is the antecedent, causes, predictor, stimulus, or input that is

introduced at the outset of the investigation.

Dependent Variables

- is the factor, property, characteristic or attribute that is measured and made the object

analysis of the study.

- Is the consequent, effect, criterion, response, or output that is analyzed and treated

statistically during investigation for purposes of hypothesis testing.

a. Independent variable as experimental. In an experiment, it may be what was caused

or what changed as result of the study. Further experimental study where a new

method of teaching, say concept mapping is introduced and tried out for a semester to

find out if it is more effective than the traditional method-lecture-demo method.

b. Independent variable is often manipulated by the researcher; in a study where one

variable causes the other. The independent variable is the cause. “In a research study,

independent variables antecedent conditions that are presumed to affect a dependent

variable. They are either manipulated by the researcher or are observed by the

researcher so that their values can be related to that of the dependent variable. For

example, the relationship between mosquitoes and mosquito bites, the number of

mosquitoes for square meter of ground would be an independent variable.

c. The independent or treatment variable is the method of teaching (lecture-demo

method versus concept mapping). The dependent variable is academic achievement

(test scores results of the two comparison groups) that will be measured and treated

statistically to find out which instructional approach is more effective.

d. The independent or grouping variable. Classification is done where objects are

assigned to groups. In a study where group are being compared, the independent

variable is the group classification.

Note: If another secondary variable is included as part of the study to determine whether it

modifies the relationship between the independent (X) and the dependent (Y) variables, it is

called the MODERATOR VARIABLES (Z). From the mentioned classification of variables

according to functional relations, we can now construct a research paradigm which will guide us

in making the objectives of the study:

Figure 1. Academic Achievement as Influenced by the Study Habits and Methods of

Teaching.

Independent Variable Method Variable Dependent Variable

VARIABLES ACCORDING TO CONTINUITY OF VALUES

1. Continuous Variables – are variables whose level can take continuous values or assume a

continuous set of numerical values. Ex. height , weight, length, width and temperature. With

these variables you can make measurement of varying degrees precision.

2. Discrete or discontinuous variables. These variables whose level cannot take the form of

decimals. The data can be taken through the process of enumeration.

Counting example: 1, 2, 2, 4 and so on.

APPLICATION OF VARIABLES CLASSIFICATION

Describing statistical variables into functional relations, continuity of values and into

scale or level of measurement will guide the researcher about how to construct a research

paradigm which portrays the interrelatedness among variables and research designs and will be

given an idea on how to use the appropriate statistical tool for data analysis procedures.

Methods of Teaching

1. Lecture – Demo2. Concept Mapping

Study Habits Academic Achievement

FUNDAMENTALS OFSTATISTICS

Independent Variable Moderator Variable Dependent Variable

Annual SalaryAnnual Salary

Educational Attainment of Father

Educational Attainment of Father

Educational Attainment of Mother

Educational Attainment of Mother

Members of the Family

Members of the Family

Type of SchoolType of School

College Entrance Score

College Entrance Score

English Performance

English Performance

Mathematics Performance

Mathematics Performance

NMAT Performance

NMAT Performance

MATI 3 – 2ND SEMESTER

S.Y. 2011-2012

IN PARTIAL FULFILLMENT

OF THE REQUIREMENT OF THE COURSE

ED 200

PHILOSOPHY IN EDUCATION

UM, DAVAO CITY

Submitted to:

LORNA T. GENERAL, Ph. D.

Submitted by:

CHRISTINE R. PAJA

MATI 3 – 2ND SEMESTER

S.Y. 2011-2012

IN PARTIAL FULFILLMENT

OF THE REQUIREMENT OF THE COURSE

ED 201

BASIC INFERENTIAL STATISTICS

UM, DAVAO CITY

Submitted to:

LORNA T. GENERAL, Ph. D.

Submitted by:

CHRISTINE R. PAJA