This document discusses sampling techniques used in research. It defines key terms like population, sample, and sampling. It describes probability sampling techniques like simple random sampling, stratified random sampling, systematic random sampling, cluster sampling, and sequential sampling. It also covers non-probability sampling techniques such as convenience sampling, purposive sampling, volunteer sampling, quota sampling, snowball sampling, and consecutive sampling. The document explains when and how to use different sampling techniques and notes important factors to consider in the sampling process.
A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.
A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.
Qualitative research is a systematic, interactive, subjective, approach used to describe life experience and give them meaning where as quantitative research is a formal, objective systematic process to describe, test relationships and examine cause and effect interaction among variables.
A pilot study as on experimental exploratory, test , preliminary , trial or try out investigation.
A trial study carried out before a research design is finalized to assist in defining the research questions or to test the feasibility, reliability and validity of proposed study design.
A small scale study conducted to test the plan and method of a research study.
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Qualitative sampling design is a key step in qualitative research, especially for rural development, researchers
this document provides the necessary details on the procedures to follow
Sampling is necessary for the researchers and nursing students....
This PPT is basically related to 4th year nursing students....
It include sampling, sample, type of population, type of sampling technique and sampling error...
Sampling is a process of selecting sample...
Sample is a representative unit of the population...
Qualitative research is a systematic, interactive, subjective, approach used to describe life experience and give them meaning where as quantitative research is a formal, objective systematic process to describe, test relationships and examine cause and effect interaction among variables.
A pilot study as on experimental exploratory, test , preliminary , trial or try out investigation.
A trial study carried out before a research design is finalized to assist in defining the research questions or to test the feasibility, reliability and validity of proposed study design.
A small scale study conducted to test the plan and method of a research study.
Observational analytical study: Cross-sectional, Case-control and Cohort stu...Prabesh Ghimire
This presentation provides overview of three observational analytical studies: cross-sectional study design, case-control study design and cohort study design
Qualitative sampling design is a key step in qualitative research, especially for rural development, researchers
this document provides the necessary details on the procedures to follow
Sampling is necessary for the researchers and nursing students....
This PPT is basically related to 4th year nursing students....
It include sampling, sample, type of population, type of sampling technique and sampling error...
Sampling is a process of selecting sample...
Sample is a representative unit of the population...
A Crux of the sampling chapter in the book: Essentials of Business Research: A Guide to Doing Your Research Project by Jonathan Wilson.
The content of the book is used under Creative Commons Attribution.
The process of using a small number of items or parts of larger population to make a conclusions about the whole population.
Sampling is the process of selecting representative units from an entire populations of a study .
Sampling is a technique of selecting a subset of the population.
EXAMPLE – While cooking rice to see whether the rice are cooked or not we never see each and every grain of rice. only a sample of rice grain is checked to make the decision regarding the cooked or the uncooked rice
A sample should be reliable.
A sample should be economical.
A sample should be goal oriented.
A sample should be appropriate in size.
A sample should be free from bias and errors.
A sample should be true representation of population.
NATURE OF THE RESEARCHER-
Inexperienced investigator
Lack of interest
Lack of honesty
Lack of adequate resources
Inadequate supervision
NATURE OF SAMPLE –
Inappropriate sampling technique
Sample Size
Defective sampling Frame
Population in statistics means the whole of the information which comes under the preview of statistical investigation.
In other words, an aggregate of objects animate or in animate under study is the population.
It is also known as “Universe”.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
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2. SAMPLING
•It is the process of selecting representative units
from an entire population of study.
This Photo by Unknown Author is licensed under CC BY-SA-NC
4. Terminology contd..
• POPULATION: it is the aggregate of all the units in which a researcher is
interested. (E.g problems faced by post graduate nurses.)
• TARGET POPULATION: it is aggregate of all the cases with certain
phenomenon about which researcher would like to make generalization.(
E.g Problems faced by post graduate nurses in Mohali.)
• ACCESSIBLE POPULATION: it is the aggregate of cases that confirm to
designated criteria and are also accessible as subjects for study. (E.g nurses
present at the time of study. Some might be on leave)
5. Terminology contd…
• SAMPLING FRAME: it is list of all the subjects in population from
which the sample is withdrawn. E.g Census
• SAMPLING: The process of selecting a portion of the population to
represent the entire population.
• SAMPLE: It is the subset of population selected to participate in
research study.
6. PURPOSE OF SAMPLING
1. ECONOMICAL: saves time, energy and resources.
2. Improved quality of data (less people , more quality in handling
people.)
3. Quick study results.
4. Precision and accuracy of data.(Interpretation of data is easy.)
7. CHARACTERISTICES OF GOOD SAMPLE
1. Representative.
2. Free from bias and errors.
3. No substitution and incompleteness.
4. Appropriate sample size.
8. SAMPLING PROCESS .. 7 steps
1. Identify and define the target population
2. Describe the accessible population and ensure sampling frame.
3. Specify the sampling unit via inclusion / exclusion criteria.
4. Specify sample selection methods.
5. Determine the sample size.
6. Specify sampling plan.
7. Selecting a desired sample.
9. FACTORS INFLUENCING SAMPLING PROCESS
NATURE OF RESEARCHER NATURE OF SAMPLE CIRCUMSTANCES
• Inexperienced
investigator
• Lack of interest
• Lack of honesty
• Intensive workload
• Inadequate supervision.
• Inappropriate sampling
technique.
• Inadequate sample size,
• Defective sampling
frame.
• Lack of time.
• Large geographic area.
• Lack of co-operation.
• Natural calamities.
10. SAMPLING TECHNIQUES
PROBABILITY SAMPLING
TECHNIQUES
NON PROBABILITY SAMPLING
TECHNIQUES
1.Simple random sampling.
2.Stratified random sampling.
3.Systematic random sampling.
4.Cluster/ multistage sampling.
5.Sequential sampling.
1.Convenient sampling.
2.Purposive sampling.
3.Volunteer sampling.
4.Consecutive sampling.
5.Quota sampling.
6.Snowball sampling.
11. Probability sampling techniques
• It is based on the theory of probability.
• It involves random selection of members from the population.
• Every subject in the population has equal chance of being selected as
study sample.
13. Simple random sampling
• Every person has an equal chance of being selected as subject.
• Population should be homogenous.
• Methods used are : lottery , table of random numbers, use of
computer.
• ADVANTAGES: most reliable, free from sampling bias.
• DISADVANTAGES: incomplete sampling frame can cause error,
expensive and time consuming.
15. Stratified random sampling
• Heterogenous population is organized in homogenous groups (strata)
e.g on the basis .
• Then random selection from each stratum is done.
• ADVANTAGES: ensures representative sample is heterogenous
population.
• DISADVANTAGES: time consuming, expensive, large population is
required, chances of faulty classification of strata.
17. Systematic random sampling
• K= N/n
• N= total number of target population.
• n= sample size
• E.g, N=300 and n=100, therefore 300/100= 3. we will be selecting
every 3rd person in the population.
• ADVANTAGES: convenient and simple, distribution of sample over
entire population.
• DISADVANATGES: sometimes may result in biased sample.
19. Cluster or multistage sampling
• Done in very large population e.g country.
• Random selection of geographical area.
• Cluster of population is selected by using simple random sampling
technique.
• ADVANTAGES: quick and easy for large population.
• DISADVANTAGES: possibility of high sampling error.
20. This Photo by Unknown Author is licensed under CC BY-SA
5. Sequential sampling
21. Sequential sampling
• Sample size is not fixed.
• Researcher initially selects small sample and tries to make inference.
• if unable to draw results, new subjects are added until clear inference
can be drawn.
• ADVANATGES: study on smallest possible sample is done.
• DISADVANTAGES: requires repeated entry in field to collect sample.
22. Non probability sampling
In this method not all population have equal chance
of getting selected as subjects.
24. Convenient sampling
• Also known as accidental sampling.
• Selection of most conveniently available people as subjects.
• Most commonly used technique in pilot studies.
• ADVANTAGES: easy, less time consuming, and economic.
• DISADVANTAGES: chances of sampling bias and same may not be
representative of entire population.
26. Purposive sampling
• Also known as judgemental or authoritative sampling.
• Samples are chosen by researcher by keeping specific purpose in
mind.
• Usually study population is limited. e.g Post disaster victims.
• ADVANTAGES: simple to draw sample and useful in exploratory
studies, saves resources and need less field work.
• DISADVANTAGES: needs adequate knowledge about population under
study, concious bias can occur therefore, the sample selected may not
a be reliable.
28. Volunteer sampling
• Participants volunteer to participate in the study.
• Researcher publishes an advertisement or inform target population
through mass media.
• ADVANTAGES: cost effective, less time and energy is required, large
data can be collected in limited time period.
• DISADVANTAGES: sample may not be representative sample and it
lacks generalizability.
30. Consecutive sampling
• Also known as Total enumerative sampling.
• It includes all the subjects that meet the inclusion criteria. e.g post
kidney transplant patients.
• The researcher conduct research one after the other until a
conclusive result is reached, thus , the prefix consecutive.
• ADVANTAGES: less energy, money and time is needed, it ensures
more representativeness of selected sample.
• DISADVANTAGES: no set plans about sample size and sampling
schedule, and there is no gurantee that representative sample will be
selected.
32. Quota sampling
• Population is divided into different groups or class.
• The groups are divided on the basis of age, gender, education level,
race, religion, and socioeconomic status.
• Percentage of groups in total population is fixed.
• ADVANTAGES: chances of reliability and generalizability are high,
suitable for studies where field work has to be carried out. e.g public
opinion polls.
• DISADVANTAGES: missing quota, over representation in sub groups,
bias is possible.
34. Snowball sampling.
• Also known as chain referral sampling.
• This technique is used to locate where subjects are hard to locate e.g
drug addicts population.
• Types of snowball sampling:
1. Linear snow ball sampling.
2. Exponential non discriminative sampling.
3. Exponential discriminative sampling.
ADVANTAGES: simple and cost effective process to locate difficult
sample
DISADVANTAGES: less control over sampling method, sample
representation is not guaranteed and sampling bias is major concern.
35. Sampling techniques used in qualitative and quantitative
research
Qualitative research
• Non probability sampling
techniques.
1. Convenience sampling
2. Snowball sampling.
3. Purposive sampling.
4. Quota sampling.
5. Consecutive sampling.
Quantitative research
• Probability sampling techniques.
1. Simple random sampling.
2. Stratified random sampling.
3. Systematic random sampling.
4. Cluster/ multistage sampling.
5. Sequential sampling.
• Non probability sampling
techniques.
40. Problems of sampling
1. Sampling error.
2. Lack of sample representativeness.
3. Difficulty in estimation of sample size.
4. Lack of knowledge about sampling process.
5. Lack of resources.
6. Lack of co-operation.
7. Lack of existing appropriate sampling frame.
8. Callous approach of researcher towards sampling process.
