This is a systematic sample in probability sampling which is consider to be one of the technics of sampling . It is most useful in certain circumstances in Random sampling.

1. Systematic Sampling
PRESENTATION BY:
SACHIN H

2. SYSTEMATIC SAMPLING
It is a type of probability sampling method
in which simple members from a large
population are selected according to
random starting point and a fixed period
interval. This interval called sampling
interval is calculated by dividing the
population size by the desired sample size

3. SYSTEMATIC SAMPLING
k = skip interval = population size(N)
sample size(n)
population size = 64
sample size = 8
k = 8

4. SYSTEMATIC SAMPLING
Steps in systematic sampling:
◦ Define the population
◦ Determine the desired sample size
◦ Obtain a list (preferably randomized) of the population
◦ Determine what K is equal to by dividing the size of the
population by the desired sample size
◦ Select some random place at the top of the population list
◦ Starting at that point, take every K th name on the list until
desired sample size is reached
◦ If the end of the list is reached before the desired sample is
reached, go back to the top of the list.

5. Example-1
Suppose a supermarket wants to study buying
habits of their customers, then using systematic
sampling they can choose every 10th or 15th
customer entering the supermarket and conduct
the study on this sample.
This is random sampling with a system. From the
sampling frame, a starting point is chosen at
random, and choices thereafter are at regular
intervals

6. Example -2
Suppose you want to sample 8 houses from a street of
120 houses. 120/8=15, so every 15th house is chosen
after a random starting point between 1 and 15. If the
random starting point is 11, then the houses selected are
11, 26, 41, 56, 71, 86, 101, and 116. As an aside, if every
15th house was a "corner house" then this corner pattern
could destroy the randomness of the population.
Population= 120 sample size= 8 K= 15

7. Note:-
Since systematic random sampling is a type
of probability sampling, the researcher
must ensure that all the members of the
population have equal chances of being
selected as the starting point or the initial
subject.

8. Thank you