It covers the topic of sampling in statistics with its types, possible ways, properties, advantages and disadvantages.

2. The process of obtaining information from a subset(sample) of a
larger group(population).
The results for the sample are then used to make estimates of
the larger group.
Faster and cheaper than asking the entire population.
SAMPLING

3.  Get information about populations
 Reduce cost of research
 More accuracy of results
 Less field time
 Generalize about population
 When it’s impossible to study the whole population
WHY SAMPLING?

4. Technical Terms
• A sampling frame is a list of sampling units.
• A sample is a collection of sampling units drawn
from a sampling frame.
• Parameters: numerical characteristics of a
population
• Statistic: numerical characteristic of a sample

5.  Probability Sample:
A method of sampling that uses of random
selection so that all units/case in the
population have an equal probability of
being chosen.
 Non-Probability Sample:
Does not involve random selection and
methods are not based on the rational of
probability theory
Sampling Techniques
Probability Non-Probability
TYPES OF SAMPLING

6. Probability SAMPLING
Following are some commonly used sampling
methods:
• Simple Random Sampling
• Stratified Random Sampling
• Cluster Sampling
• Systematic Sampling

7. SIMPLE RANDOM SAMPLING
Application when population is small,
homogeneous & readily available
All subsets of the frame are given an
equal probability. Each element of the
frame thus has an equal probability of
selection. A table of random number or
lottery system is used to determine
which units are to be selected.

8. Possible Ways To Do Sampling
• The sampling units are chosen with
replacement in the sense that the chosen
units are placed back in the population.
• The sampling units are chosen without
replacement in the sense that units are
chosen are not placed back in the
population.

9. Properties of Sample Distribution

10. Advantages:
• Easy method to use
• No need of prior information of population
• Equal and independent chances of selection to every
element
Disadvantages:
• If sampling frame large, this method impracticable.
• Does not use researcher’s expertise .
• Larger risk of random error