Multistage sampling is a complex form of cluster sampling that uses multiple sampling methods together in stages. It first divides the population into primary sampling units and randomly selects some of these units. The selected units are then divided into secondary sampling units where another random sample is selected. This process can continue for third and fourth stages if needed. Multistage sampling is commonly used in large surveys to efficiently select samples across geographical areas in multiple stages.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
01 parametric and non parametric statisticsVasant Kothari
Definition of Parametric and Non-parametric Statistics
Assumptions of Parametric and Non-parametric Statistics
Assumptions of Parametric Statistics
Assumptions of Non-parametric Statistics
Advantages of Non-parametric Statistics
Disadvantages of Non-parametric Statistical Tests
Parametric Statistical Tests for Different Samples
Parametric Statistical Measures for Calculating the Difference Between Means
Significance of Difference Between the Means of Two Independent Large and
Small Samples
Significance of the Difference Between the Means of Two Dependent Samples
Significance of the Difference Between the Means of Three or More Samples
Parametric Statistics Measures Related to Pearson’s ‘r’
Non-parametric Tests Used for Inference
SAMPLING ; SAMPLING TECHNIQUES – RANDOM SAMPLING (SIMPLE RANDOM SAMPLING)Navya Jayakumar
SAMPLING ; SAMPLING TECHNIQUES – RANDOM SAMPLING
(SIMPLE RANDOM SAMPLING)
Sampling means the process of selecting a part of the population
A population is a group people that is studied in a research. These are the members of a town, a city, or a country.
It is difficult for a researcher to study the whole population due to limited resources
E.G.. Time, cost and energy
Hence the researcher selects a part of the population for his study, rather than selecting the whole population. This process is known as sampling
Also known as Random Sampling
A type of sampling where each member of the population has a known probability of being selected in the sample
When a population is highly homogeneous, its each member has a known chance of being selected in the sample
The extend of homogeneity of a population usually depends upon the nature of the research. E.g.: who are the target respondents of the research
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
01 parametric and non parametric statisticsVasant Kothari
Definition of Parametric and Non-parametric Statistics
Assumptions of Parametric and Non-parametric Statistics
Assumptions of Parametric Statistics
Assumptions of Non-parametric Statistics
Advantages of Non-parametric Statistics
Disadvantages of Non-parametric Statistical Tests
Parametric Statistical Tests for Different Samples
Parametric Statistical Measures for Calculating the Difference Between Means
Significance of Difference Between the Means of Two Independent Large and
Small Samples
Significance of the Difference Between the Means of Two Dependent Samples
Significance of the Difference Between the Means of Three or More Samples
Parametric Statistics Measures Related to Pearson’s ‘r’
Non-parametric Tests Used for Inference
SAMPLING ; SAMPLING TECHNIQUES – RANDOM SAMPLING (SIMPLE RANDOM SAMPLING)Navya Jayakumar
SAMPLING ; SAMPLING TECHNIQUES – RANDOM SAMPLING
(SIMPLE RANDOM SAMPLING)
Sampling means the process of selecting a part of the population
A population is a group people that is studied in a research. These are the members of a town, a city, or a country.
It is difficult for a researcher to study the whole population due to limited resources
E.G.. Time, cost and energy
Hence the researcher selects a part of the population for his study, rather than selecting the whole population. This process is known as sampling
Also known as Random Sampling
A type of sampling where each member of the population has a known probability of being selected in the sample
When a population is highly homogeneous, its each member has a known chance of being selected in the sample
The extend of homogeneity of a population usually depends upon the nature of the research. E.g.: who are the target respondents of the research
sample designs and sampling procedures
,
sampling terminology
,
two major categories of sampling
,
simple random sampling
,
systematic sampling
,
cluster sampling
,
stratified sampling
,
why non probability sampling
,
errors
Biostatistics Collection of Data and Sampling Techniques SMG.pptxsajigeorge64
Biostatistics : A brief description of collection of data and sampling techniques - Methods of collection of primary and secondary data - census method- sampling methods- merits and demerits of sampling.
It will be useful for master students quantitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches.
Thank you
2. Multistage sampling is a complex form
of cluster sampling.
we use variety of sampling methods
together.
Sampling scheme that combine several
methods are called multistage samples.
3. Most survey conducted by professional
polling organization use some
combination of stratified and cluster
sampling as well as simple random
sampling.
Thus forming a multi stage random
sampling.
4. Multistage sampling refers to sampling
plans where the sampling is carried out in
stages.
Using smaller and smaller unit at each stage
5. In this method, the whole population is
divided in first stage sampling unit from
which random sample are selected.
The selected first stage is then subdivided
into second stage units from which
another sample is selected.
Third and fourth stage sampling is done in
same manner if necessary
6. Multistage designs are used in many
practical cases.
These are just a few :Large surveys
involving the sampling of housing units -
The U.S. Census Bureau selects
geographical areas within each state and
then select housing units within each
selected geographical area.
7. Practical quality control problems often
involve two (or more) stages of sampling.
For example, Ford wants to inspect the
quality of a supplier of air filters. They first
sample some cartons and then inspect
some air filters inside these selected
cartons.
Gallop poll samples approximately 300
election districts. At the second stage,
they select 5 households per district.
8. NFHS ( national family health survey) data
is collected by multistage sampling.
Rural areas2 stage sampling village
form list by PPS( probability proportional to
size), household from the village .
9. For example, household surveys conducted
by the Australian Bureau of Statistics begin by
dividing metropolitan regions into 'collection
districts' and selecting some of these
collection districts (first stage).
The selected collection districts are then
divided into blocks, and blocks are chosen
from within each selected collection district
(second stage).
Next, dwellings are listed within each selected
block, and some of these dwellings are
selected (third stage). This method makes it
unnecessary to create a list of every dwelling
in the region and necessary only for selected
blocks.
10. Advantages
Cost and speed that the survey can be
done in less.
Convenience of finding the survey sample
Normally more accurate than cluster
sampling for the same size sample
11. Disadvantages
Not as accurate as Simple Random
Sample if the sample is the same size
More testing is difficult to do