simplest way of explanation from a smart study.Sample techniques used in sampling. there are two types of techniques used in the process of sampling such as probability sampling and non probability sampling and here i have explained only Non- probability sampling.
What is Population ?
What is Sample ?
Sampling Techniques
What is Probability sampling ?
What is Non-probability sampling ?
Advantages & Disadvantages sampling
Difference b/w Probability &Non-Probability
Characteristics of sampling
This presentation educates you about Non-Probability Sampling, Types of non-probability sampling, When to use non-probability sampling?, Advantages of non-probability sampling and difference.
For topics stay tuned with Learnbay.
Probability Sampling Method- Concept - Types Sundar B N
This ppt contains Probability Sampling Method- Concept - Types which also covers Types of Sampling
Simple Random Sampling
Systematic Sampling
Stratified Random Sampling
Cluster Sampling
Reasons for Sampling
and advantages and disadvantages of each methods
simplest way of explanation from a smart study.Sample techniques used in sampling. there are two types of techniques used in the process of sampling such as probability sampling and non probability sampling and here i have explained only Non- probability sampling.
What is Population ?
What is Sample ?
Sampling Techniques
What is Probability sampling ?
What is Non-probability sampling ?
Advantages & Disadvantages sampling
Difference b/w Probability &Non-Probability
Characteristics of sampling
This presentation educates you about Non-Probability Sampling, Types of non-probability sampling, When to use non-probability sampling?, Advantages of non-probability sampling and difference.
For topics stay tuned with Learnbay.
Probability Sampling Method- Concept - Types Sundar B N
This ppt contains Probability Sampling Method- Concept - Types which also covers Types of Sampling
Simple Random Sampling
Systematic Sampling
Stratified Random Sampling
Cluster Sampling
Reasons for Sampling
and advantages and disadvantages of each methods
In research, the term sample is used to denote individuals who are observed for exposure to certain risk factors, outcomes and related variables.
Ultimately what we conclude from the sample, is often generalized to whole population from which the sample is selected.
Universe (whole population)- Entire group of the study population is known as universe or whole population. Population is often too large to cover in its entirety.
Sampling Unit- Each member of the whole population is known as sampling unit.
Sampling Frame- A list where all individuals from the whole population are drawn up is known as sampling frame.
Sample- Sample is a small representative part of the whole population.
Basic Terminologies
Population
Sample and Sampling
Advantages & Disadvantages of Sampling
Probability Sampling
Types of Probability sampling
Non-Probability Sampling
Types of Non-probability sampling
Understanding The Sampling Design (Part-II)DrShalooSaini
This Power Point Presentation has been made while referring to the research books written by eminent, renowned and expert authors as mentioned in the references section. The purpose of this Presentation is to help the research students in developing an insight about the Sampling Design(Part-II).
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
3. Introduction
Researchers commonly examine traits or
characteristics (parameters) of populations in their
studies. A population is a group of individual units
with some commonality. For example, a researcher
may want to study characteristics of female smokers in
Pakistan. This would be the population being analyzed
in the study, but it would be impossible to collect
information from all female smokers in Pakistan.
4. Therefore, the researcher would select individuals
from which to collect the data. This is
called sampling. The group from which the data is
drawn is a representative sample of the population the
results of the study can be generalized to the
population as a whole.
5. The sample will be representative of the population if
the researcher uses a random selection procedure to
choose participants. The group of units or individuals
who have a legitimate chance of being selected are
sometimes referred to as the sampling frame. If a
researcher studied developmental milestones of
preschool children and target licensed preschools to
collect the data, the sampling frame would be all
preschool aged children in those preschools.
6. Students in those preschools could then be selected at
random through a systematic method to participate in
the study. This does, however, lead to a discussion
of biases in research. For example, low-income
children may be less likely to be enrolled in preschool
and therefore, may be excluded from the study. Extra
care has to be taken to control biases when
determining sampling techniques.
7. There are two main types of sampling: probability and
non-probability sampling. The difference between the
two types is whether or not the sampling selection
involves randomization. Randomization occurs when
all members of the sampling frame have an equal
opportunity of being selected for the study. Following
is a discussion of probability and non-probability
sampling and the different types of each.
8. Probability Sampling
Uses randomization and takes steps to ensure all
members of a population have a chance of being
selected. There are several variations on this type of
sampling and following is a list of ways probability
sampling may occur:
Random sampling – every member has an equal
chance
Stratified sampling – population divided into
subgroups (strata) and members are randomly
selected from each group
9. Systematic sampling – uses a specific system to select
members such as every 10th person on an alphabetized
list
Cluster random sampling – divides the population into
clusters, clusters are randomly selected and all
members of the cluster selected are sampled
Multi-stage random sampling – a combination of one
or more of the above methods
10. Non-probability Sampling
Does not rely on the use of randomization techniques
to select members. This is typically done in studies
where randomization is not possible in order to obtain
a representative sample. Bias is more of a concern with
this type of sampling. The different types of non-
probability sampling are as follows:
11. Convenience or accidental sampling – members or
units are selected based on availability
Purposive sampling – members of a particular group
are purposefully sought after
Modal instance sampling – members or units are the
most common within a defined group and therefore
are sought after
Expert sampling – members considered to be of high
quality are chosen for participation
12. Proportional and non-proportional quota sampling –
members are sampled until exact proportions of
certain types of data are obtained or until sufficient
data in different categories is collected
Diversity sampling – members are selected
intentionally across the possible types of responses to
capture all possibilities
Snowball sampling – members are sampled and then
asked to help identify other members to sample and
this process continues until enough samples are
collected