# mrSess_17-18

Document Sample

```					Welcome
friends
SAMPLING
•   THE INTRODUCTION
•   SAMPLING TERMINOLOGY
•   CHARACTERISTICS OF GOOD SAMPLING
•   SAMPLING DESIGNS
•   SAMPLING CONCEPTS
•   CALCULATIONS OF SAMPLE SIZE
•   TYPES OF SAMPLE DESIGNS.
INTRODUCTION
• It is one of the important step in data
collection process.
• It is the process of selecting a
representative part of a population,
studying it & reaching to the conclusion.
• The basic concepts of sampling, types of
sample designs & calculation of sample
size are discussed in this chapter.
SAMPLING TERMINOLOGY

• It evolved over the   •   Element
period of its         •   Population
existence. Certain    •   Sample
factors should be
considered to set     •   Sampling unit
the sample i.e.-      •   Sampling frame
•   Parameters & statistic
•   Sampling errors
•   Sampling plan
Sampling plan
• A sampling plan is a formal method for
specifying the sampling process of
particular study:
THE NEED FOR SAMPLING-
• Resource constraints
• Accuracy
• Impossibility
• Destructive measurement
• Quality
CHARACTERISTICS OF GOOD
SAMPLING

• A good Sample should be accurate
• A good Sample should be precise
• A good Sample should be able to specify
the accuracy precision associated with it.
• It should be enable researchers to
specify the degree of confidence that can
be placed in its parameter estimate.
SAMPLING DESIGNS
• Sampling designs are of two major
types: Probability & Non-probability
methods.
• Each of these types comprises a variety
of methods of sampling.
• Probability samples are considered to be
more costly because they need a
sampling frame of entire population.
SAMPLING
CONCEPTS
CALCULATIONS
OF SAMPLE
SIZE
TYPES OF SAMPLING
•   Simple random
•   Systematic
•   Multistage random
•   Stratified
•   Cluster
•   Stratified cluster
•   Repetitive
•   Convenience
•   snowball
TYPES OF SAMPLE DESIGNS

• Simple random sampling: A sample is
chosen by using random tables or by using
computer s/w.
• Complex random sampling: various
complex method like systematic sampling,
stratified sampling methods etc. are used.
• Non-probability sampling: it is useful
when researchers may be studying only a
limited number of objectives, like dramatic
variations.
Thanks
By: Sandeep Saxena
Faculty member marketing