Here are the answers to the self-assessment questions: 1. A variable is something that varies or changes. Commonly used types are independent, dependent, intervening, extraneous, moderator and mediator variables. 2. Data refers to any information collected by the researcher for the purpose of analysis and making inferences. 3. The two main types of data are primary data and secondary data. 4. A population refers to the entire group of individuals or objects that is of interest to the researcher. 5. The target population is the entire group that the researcher wants to generalize conclusions to. 6. The accessible population is the group that the researcher can actually access and apply conclusions to. It

1. EDUCATIONAL STATISTICS
PRESENTED BY DR. HINA JALAL
Basic Statistics
Sampling
Types of Sampling
2

2. VARIABLE
The word variable is something that varies or something that is subject
to variation.
It has no definite value but can assume any set of values.
In other words we can say that a variable is a characteristic that
varies from one person to another.
It is a characteristic, number or quantity that increases or decreases
over time in different situations. 7/16/2020 4

3. V
ARIABLES
 A variable in research simply refers to a person, place, thing, or phenomenon that you are
trying to measure in some way. The best way to understand the difference between
a dependent and independent variable is that the meaning of each is implied by what the
words tell us about the variable you are using.
 There are three main variables: independent variable, dependent variable and
controlled variables.
 Main types of variables
• DEPENDENT VARIABLES.
• INDEPENDENT VARIABLES.
• INTERVENING VARIABLES.
• EXTRANEOUS VARIABLES.
• MODERATOR VARIABLES.
• MADIATOR VARIABLES.
• CONTROL VARIABLES.

4. INDEPENDENT AND DEPENDENT VARIABLES
 In research, change variables are referred as independent
variables while the outcome variables are known as dependent
variables.
 Dependent variable: called test variables, the outcome of an
experiment. When independent variable changed, what happens to
dependent variable. (achievement score)
 Independent variable: variable that has power to change
dependent variable. Plotted on the x-axis. Also called treatment
variables. 7/16/2020 14

5. INTERVENING AND EXTRANEOUS VARIABLES
 In cause effect relationship, there are some unmeasured variables affecting the
relationship. These are called extraneous variables.
 The variables linking cause-effect relationship are called
intervening variables.
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6. VARIABLE TYPES…..
 Moderating variable: changes the strength of an effect between independent
and dependent variables. For example, psychotherapy may reduce stress levels
for women more than men, so sex moderates the effect between psychotherapy
and stress levels.
 Nuisance Variable: an extraneous variable that increases variability
overall.
 Outcome variable: similar in meaning to a dependent variable, but used in a
non-experimental study.
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7. VARIABLES IN RESEARCH

8. MODERATOR VARIABLES

9. Moderator and Mediator Variables

10. DATA
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 Data is any information collected by the researcher.
 Primary Data is originated by the researcher for the first time for
addressing his research problem.
 The data can be collected using various methods like survey,
observations, physical testing, mailed questionnaire, questionnaire
filled and sent by enumerators, personal interviews, telephonic
interviews, focus groups discussion, case studies.

11. SECONDARY DATA
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.
 The information already collected and recorded by any other person
with a purpose not relating to current research problem.
 It is readily available form of data and saves time and cast of the
researcher. This data may be limited in a number of ways like
relevance and accuracy.
 Examples of secondary data are censuses data, publications, internal
records of the organizations, reports, books, websites, journal articles.

12. POPULATION AND SAMPLE
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 A research Population is a large collection of individuals or objects to
which the researcher wants to apply the study results.
 Population is the main focus of a research question. Aresearch
population is also known as a well-defined collection of individuals
or objects known to have similar characteristics.
 Sample:
 A small and representative part of individuals having same
attributes and characteristics is called sample. A sample is simply
a subset or subgroup of population

13. SAMPLE
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
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14. TYPES OF POPULATION
 The Target Population is referred to the entire group of individuals
or objects to which a researcher is interested to generalize the
conclusions. This type of population usually has varying degree of
characteristics.
 The Accessible Population is also known as the study population. It
is the population to which a researcher can apply the conclusions of
the study. This population is a subset of the target population.
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15. METHODS
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Sampling
Methods

16. PROBABILITY SAMPLING
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In probability sampling, each individual in chosen with a
known probability.
This type of sampling is also known as random sampling
or representative sampling; and depends on objective
judgment.

17. SAMPLING METHODS
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Probability Sampling
Multistage
Random Sampling
Simple Random
Sampling
Cluster Sampling
Stratified
Sampling
Systematic
Sampling

18. SIMPLE RANDOM SAMPLING
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 In random sampling each member of
the population has an equal chance
of being selected as subject.
 Each member is selected
independently of the other member of
population.
 In a commonly used method each
member of the population is assigned a
unique number. All assigned numbers are
placed in bowl and mixed thoroughly.
 The researcher, then blind-folds and picks
numbered tags from

19. SYSTEMATIC SAMPLING
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 In systematic random sampling, the researcher first randomly picks the first item or the
subject from the population. Then he selects each 9th subject from thelist.
 The procedure involved in this sampling is easy and can be done manually. The sample
drawn using this procedure is representative unless certain characteristics of the population
are repeated for every nth member, which is highly risky.

20. STRATIFIED SAMPLING
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 In this type of sampling, the whole population is
divided into disjoint subgroups.
 These subgroups are called stratum. From each
stratum a sample of pre-specified size is
drawn independently in different strata, using
simple random sampling.
 The collection of these samples constitutes a stratified
sample.

21. CLUSTER SAMPLING
A greater chance of selecting a non-
representative sample.
 In this type each sampling unit is a collection or cluster, or groups. For example, a researcher
who wants to study students may first sample groups or cluster of students such as classes,
and then, select the sample of students from among clusters.
 Advantages
Appropriate for larger population. It saves time and resources.
Disadvantages
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23. NON-PROBABILITY SAMPLING
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This technique depends on subjective judgment.
It is a process where probabilities cannot be assigned to the
individuals objectively.
It means that samples are gathered in a way does not give all
individuals in the population equal chances of being
selected.
Choose these methods could result in biased data or a limited
ability to make general inferences based on the findings.

24. SAMPLING METHODS
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Non-Probability Sampling
Judgmental
Sampling
Quota
Sampling
Convenient
Sampling
Extensive
Sampling
Snowball
Sampling

25. CONVENIENT SAMPLING
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In this technique a researcher relies on available subjects, such as
stopping peoples in the markets or on street corners as they pass by.
This method is extremely risky and does not allow the researcher to
have any control over the representativeness of the sample.
It is useful when the researcher wants to know the opinion of the
masses on a current issue; or the characteristics of people passing by
on streets at a certain point of time; or
if time and resources are limited in such a way that the research
would not be possible otherwise.

26. JUDGMENTAL OR PURPOSIVE SAMPLING
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In this technique a sample is selected on the bases of the
knowledge of population and the purpose of the study.
For example, when an educational psychologist wants
to study the emotional and psychological effects of corporal
punishment, he will create a sample that will include only
those students who ever had received corporal punishment.

27. SNOWBALL SAMPLING
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 This type of sampling is appropriate when the members of the population are difficult to locate, such as
homeless industry workers, undocumented immigrants etc.
 In snowball sample, the researcher collects data on a few members of the target population he or she can locate,
then asks to locate those individuals to provide information needed to locate other members of that population
whom they know.
 For example, if a researcher wants to interview undocumented immigrants from Afghanistan, he might
interview a few undocumented individuals he knows or can locate and from them take the address or
location of those individuals.

28. QUOTA SAMPLING
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 A quota sample is one in which units are
selected into a sample on the basis of pre-
specified characteristics so that the total
sample has the same distribution of
characteristics assumed to exist in the
population.
 For example, if a researcher wants a national
quota sample, he might need to know what
proportion of the population is male and
what proportion is the female, as well as what
proportion of each gender fall into different
age category and educational category.

29. SELF ASSESSMENTACTIVITY
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 Q. 1. Define variable. Write commonly used types of variable?
Q. 2. What do you understand by the term “data”?
Q. 3. Write down the types of data?
Q. 4. What is population?
Q. 5. What do you understand by the target population?
Q. 6. What do you mean by the assessable population?
Q. 7. What do you mean by the term “sample”?
Q. 8. Write down the types of probability sampling.
Q. 9. Write down the types of non-probability sampling.