Sampling is the process of selecting a subset of individuals from within a population to estimate characteristics of the whole population. There are several sampling techniques including simple random sampling, stratified sampling, cluster sampling, systematic sampling, and non-probability sampling. Each technique has advantages and disadvantages related to accuracy, cost, and generalizability. Proper sampling helps reduce sampling errors and increase the reliability of making inferences about the population from a sample.
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.
Formulating Hypothesis
Hypothesis Formulation is –
-the process of creating possible, tentative explanations for a given set of information.
-the whole Process of creating and formulating the hypothesis
How is Hypothesis Formulated
Reichenbach (1938) made a distinction between the two processes found commonly in any hypothesis formulation -
-Context of Discovery:
--Hypotheses is ‘discovered’ from earlier research findings, existing theories and personal observations, and experience.
-Context of justification:
--When a Researcher reconstructs his thoughts and communicates them in the form of a hypothesis to others, he uses the context of justification –
Steps in Formulation of Hypothesis
-Understand the area of problem
-Consider goal
-Identify variables
-identify the relationship between the variables.
-Think critically about hypothesis
-Express the idea as own hypothesis
Process of Hypothesis Formulation
-Understand the area of problem
Understand the problem that is being worked on.
-Consider goal
After selecting the problem & understanding the problem, objectives have to be selected according to the problem
-Identify variables
Must be define the variables.
Variables in hypothesis are testable not ?
Specify dependent and independent & others variables.
-Identify the relationship between the variables.
Variables are influence each other or not?
-Think critically about hypothesis
Hypothesis are testable, verifiable or not ? Which will make able to confirm the hypothesis.
-Express the idea as own hypothesis
Here researcher made the hypothesis in a Tentative Solution Statement manner
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.
Formulating Hypothesis
Hypothesis Formulation is –
-the process of creating possible, tentative explanations for a given set of information.
-the whole Process of creating and formulating the hypothesis
How is Hypothesis Formulated
Reichenbach (1938) made a distinction between the two processes found commonly in any hypothesis formulation -
-Context of Discovery:
--Hypotheses is ‘discovered’ from earlier research findings, existing theories and personal observations, and experience.
-Context of justification:
--When a Researcher reconstructs his thoughts and communicates them in the form of a hypothesis to others, he uses the context of justification –
Steps in Formulation of Hypothesis
-Understand the area of problem
-Consider goal
-Identify variables
-identify the relationship between the variables.
-Think critically about hypothesis
-Express the idea as own hypothesis
Process of Hypothesis Formulation
-Understand the area of problem
Understand the problem that is being worked on.
-Consider goal
After selecting the problem & understanding the problem, objectives have to be selected according to the problem
-Identify variables
Must be define the variables.
Variables in hypothesis are testable not ?
Specify dependent and independent & others variables.
-Identify the relationship between the variables.
Variables are influence each other or not?
-Think critically about hypothesis
Hypothesis are testable, verifiable or not ? Which will make able to confirm the hypothesis.
-Express the idea as own hypothesis
Here researcher made the hypothesis in a Tentative Solution Statement manner
Characteristics of a Good Sample
Representativeness
Absence of sampling error
Economically viable
Generalized and applicable
Goal oriented
Proportional
Randomly Selected
Actual information provider
Practical
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
Characteristics of a Good Sample
Representativeness
Absence of sampling error
Economically viable
Generalized and applicable
Goal oriented
Proportional
Randomly Selected
Actual information provider
Practical
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
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
entire population into different homogeneous subgroups or strata, & ...
SAMPLING METHODS
University of Pittsburgh
https://sites.pitt.edu › ~super7
PPT
Specifying a sampling method for selecting items or events from the frame; Determining the sample size; Implementing the sampling plan; Sampling and data ...
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what is sampling so explain in easy words about the sustainability and types of sustainability with examples describe suitable examples in easy words with pictures that help to understand about the 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
This slides can help the audience to know about the different sampling methods and the importance of these methods for the users.This could also help in assisting the researcher to select the appropriate method for their research to be conducted.
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2. Sampling is the process of selecting observations
(a sample) to provide an adequate description
and inferences of the population.
Sample
It
is a unit that is selected from
population
Represents the whole population
Purpose to draw the inference
Why Sample???
Sampling Frame
Listing of population from which a sample is chosen
3. What you
want to
talk about
What you
actually
observe
in the
data
Population
Sampling
Frame
Sampling
Process
Inference
Sample
4.
5.
6.
7.
8. All
subsets of the frame are given an equal
probability.
Random number generators
9. Advantages:
Minimal
knowledge of
population needed
Easy to analyze data
Disadvantages:
Low
frequency of use
Does not use researchers’ expertise
Larger risk of random error
10. Population
is divided into two or more groups
called strata
Subsamples are randomly selected from each
strata
11. Advantages:
Assures representation of all groups in
sample population
Characteristics of each stratum can be
estimated and comparisons made
Disadvantages:
Requires accurate information on
proportions of each stratum
Stratified lists costly to prepare
12. The population
is divided into subgroups (clusters) like
families.
A simple random sample is taken from each cluster
13. Advantages:
Can estimate characteristics of both cluster
and population
Disadvantages:
The cost to reach an element to sample is
very high
Each stage in cluster sampling introduces
sampling error—the more stages there
are, the more error there tends to be
14. Order
all units in the sampling frame
Then every nth number on the list is selected
N= Sampling Interval
16. Carried
out in stages
Using smaller and smaller sampling units at each
stage
Prim a ry
S e co n d a ry
Cl u s te r s
Cl u s te r s
1
1
2
2
3
3
4
5
4
5
6
7
8
6
7
9
10
11
8
9
12
13
14
10
15
Sim p le R an do m
S a m p l i n g w i th i n S e c o n d a r
17. Advantages:
More Accurate
More Effective
Disadvantages:
Costly
Each stage in sampling introduces sampling
error—the more stages there are, the more
error there tends to be
18.
19. The
probability of each case being selected from the
total population is not known.
Units
of the sample are chosen on the basis of
personal judgment or convenience.
There
are NO statistical techniques for measuring
random sampling error in a non-probability sample.
20. A.
Convenience Sampling
B.
Quota Sampling
C.
Judgmental Sampling (Purposive Sampling)
D.
Snowball sampling
E.
Self-selection sampling
21. Convenience
sampling involves choosing respondents
at the convenience of the researcher.
Advantages
Very low cost
Extensively used/understood
Disadvantages
Variability and bias cannot be measured or controlled
Projecting data beyond sample not justified
Restriction of Generalization.
22.
23. The
population is first segmented into mutually
exclusive sub-groups, just as in stratified sampling.
Advantages
Used when research budget is limited
Very extensively used/understood
No need for list of population elements
Disadvantages
Variability and bias cannot be measured/controlled
Time Consuming
Projecting data beyond sample not justified
24. Researcher
employs his or her own "expert”
judgment about.
Advantages
There is a assurance of Quality response
Meet the specific objective.
Disadvantages
Bias selection of sample may occur
Time consuming process.
25. The
research starts with a key person and
introduce the next one to become a chain
Advantages
Low cost
Useful in specific circumstances & for locating rare
populations
Disadvantages
Not independent
Projecting data beyond sample not justified
26. It
occurs when you allow each case usually
individuals, to identify their desire to take part in the
research.
Advantages
More accurate
Useful in specific circumstances to serve the purpose.
Disadvantages
More costly due to Advertizing
Mass are left
28. The
errors which arise due to the use of
sampling surveys are known as the sampling
errors.
Two types of sampling errors
Biased Errors- Due to selection of sampling
techniques; size of the sample.
Unbiased Errors / Random sampling errorsDifferences between the members of the
population included or not included.
29. Specific
problem selection.
Systematic documentation of related research.
Effective enumeration.
Effective pre testing.
Controlling methodological bias.
Selection of appropriate sampling techniques.
30.
Non-sampling errors refers to biases and
mistakes in selection of sample.
CAUSES FOR NON-SAMPLING ERRORS
Sampling operations
Inadequate of response
Misunderstanding the concept
Lack of knowledge
Concealment of the truth.
Loaded questions
Processing errors
Sample size