2. Using data to say something make an inference with
confidence, about a whole population based on the study of a
only a few sample.
A sample is a subset of all the members of a “population” or
“universe”.
3. Population: Subjects of interest
Sample: Subset for whom we have data
Statistical techniques to make conclusions
5. Results may be generalized.
Scientific ,operationally conventient and simple
in theory .
Every element in the target population has equal
probability of being chosen in the sample form
population for the survey being conducted .
7. Ever individual or item from frame has an equal
chance of being selected
Selection may be with replacement or without
replacement
Samples obtained from table of random numbers
or computer random number generators (prize
bond number)
10. 1. Dividing the population into groups, strata
2. Combining samples from each group for
total sample
11.
12. Population divided into several clusters
It is used during evident of natural grouping
All items in selected clusters can be used
13. Every element in the universe or sampling frame
not have equal probability of being choosen in
the sample form
Non-probability sampling does not involve
random selection.
15. selecting a participant or group of participants
based on their availability to the researcher
Examples
Students enrolled in the researcher’s classes
Fourth-grade students in two local, parochial schools to which the
researcher has access
16. samples that require a or an “educated guess” on the part
of the interviewer as to who should represent the
population. Also, “judges” (informed individuals) may be
asked to suggest who should be in the sample.
17. 2.3-Quota Sampling
In this case respondents are selected
according to some fixed quota relating to
gender, race, religion etc. e.g. 45% women
and 55% men.
Used when the researcher cannot use probability
sampling procedures but does want a sample that
is somewhat representative of the population
Similar to stratified sampling
18. 2.4-Snowball Sampling
A respondent is found that meets the
sampling criteria, they are asked for more
likely candidates, who are asked for more
likely candidates and so on.
