ch.9 - ppt

DR NEENA DR DEEPAK CHAWLA SONDHI

CHAPTER-9 SAMPLING CONSIDERATIONS

RESEARCH

CONCEPTS AND

SLIDE 9-1

DR NEENA

Sampling Concepts  Population: Population refers to any group of people or objects that form

the subject of study in a particular survey and are similar in one or more ways.  Element: An element comprises a single member of the population.

DR DEEPAK CHAWLA SONDHI

 Sampling frame: Sampling frame comprises all the elements of a

population with proper identification that is available to us for selection at any stage of sampling.  Sample: It is a subset of the population. It comprises only some elements

of the population.  Sampling unit: A sampling unit is a single member of the sample.  Sampling: It is a process of selecting an adequate number of elements

from the population so that the study of the sample will not only help in understanding the characteristics of the population but will also enable us to generalize the results.  Census (or complete enumeration): An examination of each and every

element of the population is called census or complete enumeration.

RESEARCH

CONCEPTS AND

DR NEENA

Advantages of Sample over Census

SLIDE 9-2

 Sample saves time and cost.  A decision-maker may not have too much of time to

DR DEEPAK CHAWLA SONDHI

wait till all the information is available.

 There are situations where a sample is the only option.  The

study of a sample instead of complete enumeration may, at times, produce more reliable results.

A census is appropriate when the population size is small.

RESEARCH

CONCEPTS AND

SLIDE 9-3

DR NEENA

Sampling vs Non-Sampling Error  Sampling error: This error arises when a sample is not

representative of the population.

 Non-sampling error: This error arises not because a sample is

DR DEEPAK CHAWLA SONDHI

not a representative of the population but because of other reasons. Some of these reasons are listed below: 

Plain lying by the respondent.

 The error can arise while transferring the data from the questionnaire to the

spreadsheet on the computer.

 There can be errors at the time of coding, tabulation and computation.  Population of the study is not properly defined  Respondent may refuse to be part of the study.  There may be a sampling frame error.

RESEARCH

CONCEPTS AND

SLIDE 9-4

DR NEENA

Sampling Design

DR DEEPAK CHAWLA SONDHI

Probability Sampling Design - Probability sampling designs are used in conclusive research. In a probability sampling design, each and every element of the population has a known chance of being selected in the sample. Types of Probability Sampling Design Simple random sampling with replacement Simple random sampling without replacement Systematic sampling Stratified random sampling Cluster sampling

RESEARCH

CONCEPTS AND

SLIDE 9-5

DR NEENA

Sampling Design

DR DEEPAK CHAWLA SONDHI

Non-probability Sampling Designs - In case of non-probability sampling design, the elements of the population do not have any known chance of being selected in the sample. Types of Non-Probability Sampling Design Convenience sampling Judgemental sampling Snowball sampling Quota sampling

RESEARCH

CONCEPTS AND

SLIDE 9-6

DR NEENA

Determination of Sample Size The size of the population does not influence the size of the sample

DR DEEPAK CHAWLA SONDHI

Methods of determining the sample size in practice: Researchers may arbitrary decide the size of sample without

giving any explicit consideration to the accuracy of the sample results or the cost of sampling. The total budget for the field survey in a project proposal is

allocated.

Researchers may decide on the sample size based on what

was done by the other researchers in similar studies.

RESEARCH

CONCEPTS AND

SLIDE 9-7

DR NEENA

Determination of Sample Size Confidence interval approach for determining the size of the sample

DR DEEPAK CHAWLA SONDHI

The following points are taken into account for determining the sample size in this approach. The variability of the population: Higher the variability as

measured by the population standard deviation, larger will be the size of the sample. The confidence attached to the estimate: Higher the confidence

the researcher wants for the estimate, larger will be sample size.

The allowable error or margin of error: Greater the precision the

research seeks, larger would be the size of the sample.

RESEARCH

CONCEPTS AND

SLIDE 9-8

DR NEENA

Determination of Sample Size

DR DEEPAK CHAWLA SONDHI

Sample size for estimating population mean The formula for determining sample size is given as:

Where

n = Sample size σ = Population standard deviation e = Margin of error Z = The value for the given confidence interval

RESEARCH

CONCEPTS AND

SLIDE 9-9

DR NEENA

Determination of Sample Size

DR DEEPAK CHAWLA SONDHI

Sample size for estimating population proportion – 1. When population proportion p is known

2. When population proportion p is not known

RESEARCH

CONCEPTS AND

DR NEENA DR DEEPAK CHAWLA SONDHI

END OF CHAPTER

RESEARCH

CONCEPTS AND