Docstoc

mrSess_17-18

Document Sample
mrSess_17-18 Powered By Docstoc
					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
   HQ, Hyderabad

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:12
posted:9/15/2012
language:
pages:12