Presentation on Sample Design

2. Sample Design
• A sample design is framework, or road map, that serves as base for
selection of a survey sample and affects many other important aspects
of a survey as well. For example, a researcher may want to interview
males through a telephone survey.
• Selection of a suitable sample design method ensures that the samples
you invest time and money into collecting can support the
inferences you want to make.

3. Implication of a sample design
• A sample design is a definite plan for obtaining a sample from given
population.
• Technique or the procedure researcher would adopt in selecting items.
• Sample design is determined before data are collected.
• Researcher must select sample design which should be reliable and
appropriate for the study.

4. Steps in Sample Design
Sample design is the heart of research work
• Define the universe
• Sampling unit
• Source list or sampling frame
• Size of sample
• Sampling method or technique
• Parameters of interest
• Budgetary constraints
• Select the sample

5. Methods/Types of Sampling
Samples may be grouped into broad classes according to their method of
selection. Namely:
• Random or Probability Sampling: Involves random selection, allowing
you to make statistical inferences about the whole group.
• Non-Random or Non-Probability Sampling: Involves non-random
selection based on convenience or other criteria, allowing you to easily
collect initial data.

6. Random or Probability Sampling
Major random or probability samples are:
• Simple random sample
• Systematic sample
• Stratified random sample
• Multi-stage random sample
• Cluster sample or area sample
• Sequential sample or sample in instalments
• Replicated or interpenetrating sample

7. Non-Random or Non-Probability Sampling
Major Non-random or Non-probability samples are:
• Purposive sample
• Quota sample
• Convenience sample

8. Criteria for selecting a sampling procedure
In selecting a sampling procedure must remember that two costs are involved in
a sampling analysis:
• The cost of collecting data and,
• The cost of an incorrect inference resulting from the data.
Researcher must keep in view two causes of incorrect inferences: systematic bias
and sampling error

9. Characteristics of a good sample design
• Sample design must result in a truly representative sample.
• Sample design must be viable in the context of funds available for the research
study.
• Sample design must be such so that systematic bias can be controlled in a better
way.
• Sample should be such that the results of the sample study can be applied, in
general, for the universe with a reasonable level of confidence.

10. Measurement scales
Scales of measurement in research and statistics are different ways in which variables are
defined and grouped into different categories. It describes nature of values assigned to variables
in a data set.
Scaling Techniques
Scaling technique is a method of placing respondents in continuation of gradual change in pre-
assigned values, symbols or numbers based on the features of a particular object as per the
defined rules:
•Paired Comparison
•Rank Order
•Constant Sum
•Q-Sort Scaling
•Continuous Rating Scales
•Itemized Rating Scale