The document explains the concepts of population and sample in research, defining a population as the entire group of interest and a sample as a subset of that group. It describes two main sampling methods: probability sampling, which ensures equal chances of selection, and non-probability sampling, which can lead to bias. The conclusion emphasizes the importance of a representative sample to avoid biased outcomes.

1. CONCEPT OF POPULATION
AND SAMPLE
BY- SUJIT KUMAR BHOI

2. WHAT IS POPULATION ?
In research, a population is the
entire group of people, objects,
events, or organizations that are of
interest to the researcher. The
population is defined based on the
research objectives and the specific
parameters or attributes under
investigation.

3. WHAT IS SAMPLE?
sample is a subset of individuals from a
larger population. Sampling means selecting
the group that you will actually collect data
from in your research. For example, if you
are researching the opinions of students in
your university, you could survey a sample
of 100 students..

6. PROBHABILITY SAMPLING
Each member of the population has
an equal chance of being selected
for the sample. This method is
often used in public opinion
studies and election polling.
Probability sampling methods
include simple random sampling,
stratified sampling, systematic
sampling, and cluster sampling.

7. NON PROBABILITY
SAMPLING
Nonprobability sampling is a method
of selecting a sample group from a
population that doesn't use random
sampling techniques. It's a quick,
inexpensive way to gather data, but
it can lead to biased results

8. CONTINUE
Convenience sampling, where participants are
selected based on their availability and
convenience
Quota sampling
Purposeful sampling, which includes
heterogeneity sampling, homogeneous
sampling, deviant sampling, and expert
sampling

9. CONCLUSION
The sample must be representative of the
population. A representative sample is a
subset of the population that reflects the
characteristics of the population. A
sample is biased if it systematically favors
a certain outcome. Random selection
eliminates bias.

10. THANK YOU
VERY MUCH!