Ch.9 - Ppt j5l64
This document was ed by and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this report form. Report 3b7i
Overview 3e4r5l
& View Ch.9 - Ppt as PDF for free.
More details w3441
- Words: 809
- Pages: 11
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 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
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 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
Related Documents 3m3m1z
Ch9 5t2r6f
November 2019 54
Ch9 5t2r6f
November 2019 44
P2 - Guerrero Ch9 4h1qp
October 2020 0
Lec8 Ch9 Process Model Dfd 566f5e
March 2021 0
Williamson Macroeconomics Ch9 Solutions 6e495i
December 2019 57
Ch9-ques-2013 s5b5r
December 2019 36More Documents from "Arnold Sargunam" 3n5p6a
Ch.9 - Ppt j5l64
December 2019 48
Pml Moving And Rotation Animation Of Aveva E3d-pdms 5f95l
April 2020 39
Pdms Pml Manual - 2 6f2k69
November 2021 0
Articolul 11 4d464z
August 2021 0
Auxiliar Contable Dinamica De Cuentasv.1 335r3s
October 2020 0