This document discusses simple random sampling, which is a type of probability sampling technique where each member of the population has an equal chance of being selected. It provides examples to illustrate simple random sampling, such as selecting sugar from a bag or using a lottery system or random number table to randomly pick sample members. The key aspects of simple random sampling are that selection is random and does not depend on the characteristics of the population members, giving each member an equal chance of selection.

1. SAMPLING ; SAMPLING TECHNIQUES –
RANDOM SAMPLING
(SIMPLE RANDOM SAMPLING)
PRESENTED BY,
NAVYA JAYAKUMAR P
REG NO: MBA105/18

2. INTRODUCTION
• Sample : the selected part of population
• Sample Size : the number of people in the selected
sample
• Sampling Frame: the list of individual or people
included in the sample
• Sampling : the process of selecting a part of the
population
• Sampling Technique : the technique or procedure
used to select the members of the sample. There are
various types of sampling techniques

3. SAMPLING
• Sampling means the process of selecting a part of the
population
• A population is a group people that is studied in a
research. These are the members of a town, a city, or a
country.
• It is difficult for a researcher to study the whole
population due to limited resources
E.G.. Time, cost and energy
• Hence the researcher selects a part of the population for
his study, rather than selecting the whole population.
This process is known as sampling

4. EXAMPLE

5. TYPES OF SAMPLING
There are mainly two types of sampling
1.probability sampling
– Simple random sampling
– Stratified Random Sampling
– Systematic Random Sampling
– Cluster (Area) Random Sampling
– Multi-Stage Sampling
2.Non-probability sampling
– Purposive sampling
– Quota Sampling
– Convenience Sampling
– Snowball Sampling

6. PROBABILITY SAMPLING
• Also known as Random Sampling
• A type of sampling where each member of the
population has a known probability of being
selected in the sample
• When a population is highly homogeneous, its each
member has a known chance of being selected in the
sample
• The extend of homogeneity of a population usually
depends upon the nature of the research. E.g.: who
are the target respondents of the research

7. EXAMPLE
•If we want to pick some sugar from any part of a
bag containing sugar, the selected part will have
similar characteristics.
•In such a case, each member has a known chance
of being selected in a sample.
•Hence, the sample collected from any part of a bag
containing sugar will be a true representative of the
whole sugar.
•In such a situation probability sampling is
adopted.

8. SIMPLE RANDOM SAMPLING
• The members of the sample are selected randomly and
purely by chance
• As every member has an equal chance of being
selected in the sample, random selection of members
does not affect the quality of the sample.
• Hence the members are randomly selected without
specifying any criteria for selection
• Sometimes the researcher may use a lottery system to
select the members randomly
• Simple random sampling is a suitable technique for a
population which is highly homogeneous

9. BINGO BALLS COMING OUT OF A BINGO MACHINE

10. TYPES
• There are two ways of creating a simple
random sample. These include:
– The lottery method,
– Random number table

11. LOTTERY METHOD
• Each Number Placed in a card of similar size,
shape and colour
• Cards put in a bowl & thoroughly mixed
• Blindfolded person selects a card
• Process Repeated till we reach the desired
Sample Size

12. EXAMPLE

13. RANDOM NUMBER TABLE
• A random number table is a series of digits (0 to
9) arranged randomly in rows and columns.
• The table usually contains 5-digit numbers,
arranged in rows and columns, for ease of
reading.
• You will find random number tables in most
statistical textbooks.
• Random number tables have been in existence
since 1927 and are generated by a variety of
methods.

15. EXAMPLE
1. Assume you have the test scores for a population of 200 students. Each
student has been assigned a number from 1 to 200. We want to randomly
sample only 5 of the students for this demo.
2. Since the population size is a three-digit number, we will use the first
three digits of the numbers listed in the table.
3. Without looking, point to a starting spot in the table. Assume we land on
75636 (3rd column, 2nd entry).
4. This location gives the first three digits to be 756. This choice is too large
(> 200), so we choose the next number in that column. Keep in mind that
we are looking for numbers whose first three digits are from 001 to 200
(representing students).
5. The second choice gives the first three digits to be 407, also too large.
Continue down the column until you find 5 of the numbers whose first
three digits are less than or equal to 200.
6. From this table, we arrive at 070 (07015), 038 (03811), 045 (04594), 055
(05542), and 194 (19428).
7. RESULT: Students 38, 45, 55, 70, and 194 will be used for our random
sample.