CONCEPT OF POPULATION AND SAMPLE

Abstract

This paper deals with the concept of Population and Sample in research, especially in educational and psychological researches and the researches carried out in the field of Sociology, Commerce and Humanities. Basic types of population and sample are also discussed briefly in it.

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CONCEPT OF POPULATION AND SAMPLE
Generally, inferential statistics is used in quantitative type of educational, psychological
and sociological researches. For that, research is carried out on selected sample and the results
are generalised on a large or entire group of targeted subjects. Such a group is called population
in research. The researcher has to decide and define the population accurately before starting
research activities. Well defined population helps the researcher in selecting sample of proper
size, which represents the entire population. Success of research and reliability of results mostly
depend upon the sample. How to select such sample that represents the entire population in real
sense is discussed in this chapter. Let’s start with the meaning of population.
POPULATION
Any type of research has been based on objectives. Objectives, clarify the subjects of
study directly or indirectly. On which group the results of research can be applied or for which
group the findings can be generalised is clarified by the objectives of study. Such group is
known as population in research. However, some researchers use the word ‘universe’ in place
of ‘population’, but there is a minute difference between these two. It can be clarified by
referring the definitions and meaning of both.
Definition of Universe
Universe refers to the set of all the units, which possess a variable characteristic under
study.
Meaning of Universe
Referring to the definition of universe, we can say that it is a group or set of all such units
that possess the variable characteristic under study. Until and unless clarification is given,
universe accommodates all the units that possess the characteristic to be studied and have
existence in entire universe or in the area of research.
E.g. In a study of achievement motivation of the students of grade eight of Ahmedabad
in the context of their study habits, set of all the students of Ahmedabad, who are studying in
grade eight will be considered as universe, irrespective of their medium of instruction.
Achievement motivation and study habits are the variables of study and students of grade
VIII form the universe of the study in this example.
Depending upon the objectives of research, anything can be taken as a unit of study out
of Person, Object, Living Beings, Time, Incident, Occasion, Words, Sentences, Place, Society,
and Institution.
Definition of Population
Population refers to the set or group of all the units on which the findings of the research
are to be applied.
Meaning of Population
Referring to the definition of population, we can say that it consists of all the units on
which the findings of research can be applied. In other words, population is a set of all the units
which possess variable characteristic under study and for which findings of research can be
generalised.
In the earlier mentioned example, if findings of the research are restricted to be applied
only on Gujarati medium students of grade eight of Ahmedabad city, the population will consist
of only Gujarati medium students of grade eight of Ahmedabad city.
Population may clearly be defined in statement of the problem also. If it is clearly defined
in research title, universe may not be there in research.

See the following examples of research problem.
 Achievement motivation of the students of grade eight of Ahmedabad in the context of
their study habits,
 Achievement motivation of the Gujarati medium students of grade eight of Ahmedabad
in the context of their study habits,
In the first example, the universe consists of all the students of grade eight of Ahmedabad
city. If researcher does not limit his study, this universe will be population also. If he limits his
study to Gujarati medium students, the universe will include all the students of grade eight and
population will include only Gujarat medium students.
In the second example, researcher clearly mentions the population in the title. Here
universe and population will be the same. In this case also, if he limits his study to the students
of grant in aided schools, the population will include Gujarati medium grade eight students of
grant in aided schools of Ahmedabad city and universe will include all Gujarati medium
students of grade eight of Ahmedabad city.
On the basis of this discussion, it is revealed that researcher must finalise population of
the study well in advance before starting research activities, so that he can plan the process
properly and implement it easily and without any hindrance.
We have seen that there is a noticeable difference between population and universe, but
many scholars use both as alternative of each other in practical life.
Besides having understanding of population and universe, researcher must have clear
knowledge of different types of population.
TYPES OF POPULATION
Here some important types of population are discussed, but remember this is not a final
classification because different scholars have classified it on the basis of different criteria. The
most common classification is given here.
Finite and Infinite Population
The population in which number of units is finite and can be counted precisely, is called
finite population. The following are some examples of the same.
 Population of the students who appeared in S. S. C. Exam in Gujarat in March 2017.
 Students enrolled in Post Graduate courses in Gujarat.
 In service primary teachers of Rajasthan.
The population, in which the number of units is infinite and cannot be counted is called
infinite population. The following are some examples of the same.
 Decimal numbers lying between integers 1 and 2.
 Number of stars in the sky.
 Words formed by using all English alphabets.
 Number of cells in human body.
Homogeneous and Heterogeneous Population
If all the units of population are identical or similar in terms of certain characteristic/s, it
is called homogeneous population. Such a population is not found in the areas of social science,
education and psychology but found in basic and pure science. However, by applying some
statistical methods, population is made homogeneous in social sciences, education and
psychology.
Blood in a living being, crop produced in a particular farm, DNA of persons having blood
relation, water in a particular vessel and atoms in a particular element are the examples of
homogeneous population. Testing a single drop of blood reveals the condition of blood of
whole body, one can predict the quality of grain produced in a farm by checking a small

quantity of grain, by matching the DNA of two persons one can decide whether they have blood
relation or not. This is possible because a small part of a whole, represents it completely.
If all the units of population differ completely or in some aspects with one another, the
population is called heterogeneous population.
All students of the same school and class differ from one another in different mental and
physical abilities. This is an example of heterogeneous population. Such population is found in
education, psychology, social sciences and humanities.
Existent and Hypothetical Population
If the units of population have physical existence, it is called existent population. Finite
and existent populations can be considered as alternative of each other in most of the cases.
Students and teachers in a city, district or state is the example of such a type of population.
Members in a family, working women in a city, children having autism or dyslexia in a part of
city are other examples of existent population.
The population, units of which do not have physical existence but their existence is
assumed or probability of their existence is found by statistical method is called hypothetical
population. Such population is also known as statistical population. Probability of such
population is decided on the basis of repetition of some incident in past or with the help of
statistical calculation.
Some examples of such population are as follows.
 A population showing the lifespan of electric bulbs produced in some factory. Lifespan
of the bulbs assumed on the basis of durability period of bulbs produced and used in past.
Exact life of such items cannot be predicted precisely.
 Maximum and minimum temperature of different cities can be assumed on the basis of
past experience. It cannot be predicted precisely.
 Population showing the probability of number of Heads found by tossing a coin many
times. Here, one cannot say exactly that how many times Head will occur, if a coin is
tossed 5 times, but he can assume that either 1, 2….. or 5 times Head can come.
Known and Unknown Population
If the parameter of the population are known, it is called known population. (Parameter
refers to statistical measurement taken from the data from the entire population.)
E.g. In the study of achievement of the students appeared in S. S. C. examination in 2019-
2020, the set of all the students appeared in SSC exam in that year will be called known
population because the average marks of all these students and standard deviation of their
marks can be calculated or known easily.
If the parameter of population is unknown or cannot be calculated easily, it is known as
unknown population.
E.g. In the study of intelligence of secondary school students of Gujarat, the population
will be of unknown type because average marks and standard deviation of scores of the students
in intelligence test are not easily available and cannot be calculated easily because this
population consists of a large number of students.
Such unknown population is targeted in most of educational, psychological and
sociological researches.
It is a quite clear and known fact that in most of the researches in any field, data are
collected from sample instead of from population and findings of the same is generalised on
the entire population. Therefore, in order to get precise result of research, sample has to be
selected by taking extreme care. Let’s discuss how it is possible.
DEFINITIONS OF SAMPLE

Some definitions of sample are as follows.
 Sample is a reprehensive part of a population of research.
 Any sub set of population, which represents all the types of elements of population is
called sample.
 Sample refers to the small amount of something that gives the information about the
thing, it is taken from.
Now we will discuss the meaning of sample.
MEANING OF SAMPLE
A part of population that represents it completely is known as sample. It means, the units,
selected from the population as a sample, must represent all kind of characteristics of different
types of units of population.
Due to various reasons, data are collected from units of sample instead of all units of
population in majority of researches and their findings are generalised in the context of entire
population. This can be done precisely only if the efforts are made to select the sample by
keeping in mind the characteristics of an ideal sample.
CHARACTERISTICS OF AN IDEAL / GOOD SAMPLE
Characteristics of an ideal sample are as follows.
 Number of units in sample must be proportionate. It means a size of sample must be in
proper proportion of number of units in population.
 Units selected in sample must represent all the characteristics of different units of
population.
 Sample should be helpful in realising all the objectives of research.
 Units of sample must be selected fairly without any bias. It means all the units of
population must have equal chance to be selected in sample.
 Sample should be such, that can save time, energy and money of researcher.
 Contact of units of sample should be convenient for researcher. It means, units of sample
should be within the reach of researcher.
 Collection of data from units of sample should be convenient for researcher.
Selection of such sample makes the task of researcher easy and precise. Therefore sample
is very much important in research.
IMPORTANCE OF SAMPLE
Importance, need or utility of sample in research can be described as discussed here.
 Research process becomes faster and less expensive
 Research process can be completed precisely, as number of subjects in sample has been
less than that in population.
 Data can be collected easily for research.
 Statistical Measurements can be taken easily and precisely because number of subjects
in sample has been comparatively less.
 Data collection and research process remain under the control of the researcher, as he has
to collect data from, and deal with, less number of subjects.
 Data analysis and interpretation can be done precisely.
 If the subjects are to be demolished for collecting data, sample selection is the only way
for conducting research. Research, done to know the life span of electric bulb or to know
the blood group of a person or to test the taste of cold drink are such type of researches.

 Sample is essential in experimental research because it is a complex process and data
collection process in such research consumes more time. So collecting data from entire
population becomes tedious and impractical.
 In the same way, in longitudinal studies, engaging all units of population for a long time
period for research purpose becomes tedious and impractical. So, sample selection
becomes essential in such researches.
 If approaching all units of population that spread over large geographical area becomes
impractical, the researcher has to collect data from sample.
 If it is difficult to collect information about all units of population, sample selection
becomes inevitable.
 In the case of infinite population, data can be collected from sample only.
 Face to face contact between researcher and subjects becomes easy and convenient if
sample is selected for research.
 Complex and sensitive tools can be used safely for research, as subjects can be made
aware of sensitivity of the same properly because they have been comparatively less in
number.
Researcher has to select the sample properly, so that accurate data can be collected for
research. For that, researcher has to keep in mind the feasibility of selecting ideal sample. If it
is impossible, he can compromise with accuracy of selecting sample in unavoidable conditions.
He can apply certain type of sampling method in certain type of condition. How? We will
discuss now. But before that we shall clarify the concept of Sampling.
MEANING OF SAMPLING
The process of selecting sample from population is called sampling. A method used to
select a sample is called sampling method.
Researcher can apply certain sampling method out of different methods according to the
objective of research. TYPES OF SAMPLING METHOD
Different sampling methods are categorised mainly in two groups as (i) Probability
Sampling Method and (ii) Non-Probability Sampling Method.
MEANING OF PROBABILITY SAMPLING METHOD
A sampling method, in which subjects are selected without any bias or prejudice and in
which all the units of population have equal or predetermined and certain probability to be
selected in a sample, is known as probability sampling method.
E.g. For selecting one student out of ten, if chits with their names are prepared and one
chit is taken out of them, all the students will have equal chance to be selected. The probability
of all students of being selected will be .1 or 1/10.
In this way, units of population have certain chance or fixed probability to be selected in
a sample. The subjects are selected without any bias or prejudice in this method.
It is considered as the best method of selecting a sample due to its some specific
characteristics.
SPECIAL FEATURES OF PROBABILITY SAMPLING METHOD
The characteristics of probability sampling are as follows.
 Subjects are selected in an objective and unbiased manner.
 Each unit of population has certain probability to be selected in a sample. (In our earlier
mentioned example it is 1/10 or .1.)
 Value of such probability is fixed before selecting the sample.
 Researcher can select a sample by keeping in mind the size of the sample by applying

suitable method of probability sampling.
 Researcher’s personal wish does not affect the selection of a certain subject.
 Every subject is selected independently.
 Selection of one subject does not affect the selection of another subject.
 It increases the possibility of selecting such a sample that represents the population
completely.
 It is very helpful in determining sampling error. It means it makes easy to know the
difference between statistics and parameter.
 Confidence level of results can be determined properly.
NON-PROBABILITY SAMPLING METHOD
This method of sample selection does not have any scientific base, so it increases the
chances of selecting biased sample. In most of the cases, such sample does not represent all
characteristics of entire population.
All units do not have certain or fixed probability to be selected in sample in this method.
That is why, this is known as non-probability sampling method.
E.g. Researcher selects one student out of ten, according to his wish or selects a student
whoever is seen first.
SPECIAL FEATURES OF NON-PROBABILITY SAMPLING METHOD
The following are special features (Characteristics) of non-probability sampling.
 Subjects are selected in sample in subjective manner.
 All units of population do not have certain probability to be selected in sample.
 Personal wish or willingness of researcher affects the selection of subjects in a sample.
 It increases the chance of selecting such sample that does not represent the population
entirely.
Some units of population may have more chance to be selected in sample than others.
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