The document discusses various sampling methods used in statistical analysis and research. It explains that sampling is necessary when studying large populations as it is not feasible to study the entire population. It then describes different types of probability sampling methods like simple random sampling, cluster sampling, systematic sampling, and stratified random sampling. It also discusses non-probability sampling methods and their uses in exploratory research. The document highlights advantages of probability sampling in obtaining unbiased results and representing population demographics. It further notes potential sources of bias and errors in sampling.
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
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
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.
Probability Sampling and Types by Selbin Babuselbinbabu1
The presentation will cover probability sampling and all the types of probability sampling like Random sampling , systematic random sampling, strtified random sampling, cluster random sampling and multi stage sampling.
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.
Probability Sampling and Types by Selbin Babuselbinbabu1
The presentation will cover probability sampling and all the types of probability sampling like Random sampling , systematic random sampling, strtified random sampling, cluster random sampling and multi stage sampling.
Sampling - Types, Steps in Sampling process.pdfRKavithamani
Sampling is a technique of selecting individual members or a subset of the population to make statistical inferences from them and estimate the characteristics of the whole population. Different sampling methods are widely used by researchers in market research so that they do not need to research the entire population to collect actionable insights.
Sampling and different ways of sampling under public opinion and survey research.Advantages and disadvantages of different sampling methods with pictures and examples.
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a PowerPoint about research analysis on the diversity of a certain organisms in a specific place and their abundance and environmental factors that could possibly affect their existence in the area
this document also includes the presentation of my group and a comprehensive analysis on lichen life in the baranggay
unfortunately it's not the final research for this paper so all the details are not yet to include tho alot of important information were included so that a general understanding of he topic is expected to be explained very well including all the important details
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
QA Paediatric dentistry department, Hospital Melaka 2020Azreen Aj
QA study - To improve the 6th monthly recall rate post-comprehensive dental treatment under general anaesthesia in paediatric dentistry department, Hospital Melaka
We understand the unique challenges pickleball players face and are committed to helping you stay healthy and active. In this presentation, we’ll explore the three most common pickleball injuries and provide strategies for prevention and treatment.
Struggling with intense fears that disrupt your life? At Renew Life Hypnosis, we offer specialized hypnosis to overcome fear. Phobias are exaggerated fears, often stemming from past traumas or learned behaviors. Hypnotherapy addresses these deep-seated fears by accessing the subconscious mind, helping you change your reactions to phobic triggers. Our expert therapists guide you into a state of deep relaxation, allowing you to transform your responses and reduce anxiety. Experience increased confidence and freedom from phobias with our personalized approach. Ready to live a fear-free life? Visit us at Renew Life Hypnosis..
How many patients does case series should have In comparison to case reports.pdfpubrica101
Pubrica’s team of researchers and writers create scientific and medical research articles, which may be important resources for authors and practitioners. Pubrica medical writers assist you in creating and revising the introduction by alerting the reader to gaps in the chosen study subject. Our professionals understand the order in which the hypothesis topic is followed by the broad subject, the issue, and the backdrop.
https://pubrica.com/academy/case-study-or-series/how-many-patients-does-case-series-should-have-in-comparison-to-case-reports/
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
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In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
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The speakers included:
Professor Orazio Schillaci, Minister of Health, Italy
Dr Hans Groth, Chairman of the Board, World Demographic & Ageing Forum
Professor Ilona Kickbusch, Founder and Chair, Global Health Centre, Geneva Graduate Institute and co-chair, World Health Summit Council
Dr Natasha Azzopardi Muscat, Director, Country Health Policies and Systems Division, World Health Organisation EURO
Dr Marta Lomazzi, Executive Manager, World Federation of Public Health Associations
Dr Shyam Bishen, Head, Centre for Health and Healthcare and Member of the Executive Committee, World Economic Forum
Dr Karin Tegmark Wisell, Director General, Public Health Agency of Sweden
2. Sampling plays an important role in the field of Research and statistics
and we should know the basic concept of it.
Sampling is a method used in statistical analysis of a data where a
specific number of samples are taken from a population for a study.
In the case of an infinite population, it is not possible to do on the
whole population. In such cases, a sample study is the only applicable
method.
3. For e.g. a manufacturer industry wants to check the quality of
a product. It is not possible to check on each and every item
is manufactured. So we will take some part of it for inspecting
the quality.
Sampling is a technique of selecting individual members or a
subset of the population to make statistical inferences from
them and estimate characteristics of the whole population.
4.
5. Sampling in market research is of two types – probability sampling
and non-probability sampling. Let’s take a closer look at these
two methods of sampling.
Probability sampling:. All the members have an equal opportunity
to be a part of the sample with this selection parameter.
Non-probability sampling: This sampling method is not a fixed or
predefined selection process. This makes it difficult for all
elements of a population to have equal opportunities to be
included in a sample.
6. Probability sampling is a sampling technique in which researchers
choose samples from a larger population using a method based on the
theory of probability.
This sampling method considers every member of the population and
forms samples based on a fixed process.
For example, in a population of 1000 members, every member will have
a 1/1000 chance of being selected to be a part of a sample.
Probability sampling eliminates bias in the population and gives all
members a fair chance to be included in the sample.
7.
8. One of the best probability sampling techniques that helps in
saving time and resources, is the Simple Random Sampling method.
Each individual has the same probability of being chosen to be a
part of a sample.
For example, in an organization of 500 employees, if the HR team
decides on conducting team building activities, it is highly likely
that they would prefer picking chits out of a bowl. In this case, each
of the 500 employees has an equal opportunity of being selected.
9. Cluster sampling is a method where the researchers divide the entire
population into sections or clusters that represent a population.
Clusters are identified and included in a sample based on demographic
parameters like age, sex, location.
For example, if the United States government wishes to evaluate the
number of immigrants living in the Mainland US, they can divide it into
clusters based on states such as California, Texas, Florida,
Massachusetts, Colorado, Hawaii, etc. This way of conducting a survey
will be more effective as the results will be organized into states and
provide insightful immigration data.
10. Researchers use the systemic sampling method to choose the
sample members of a population at regular intervals.
This type of sampling method has a predefined range, and
hence this sampling technique is the least time-consuming.
For example, a researcher intends to collect a systematic sample
of 500 people in a population of 5000. He/she numbers each
element of the population from 1-5000 and will choose every
10th individual to be a part of the sample (Total population/
Sample Size = 5000/500 = 10).
11. Stratified random sampling is a method in which the researcher divides
the population into smaller groups that don’t overlap but represent the
entire population.
While sampling, these groups can be organized and then draw a sample
from each group separately.
For example, a researcher looking to analyze the characteristics of
people belonging to different annual income divisions will create strata
(groups) according to the annual family income. Eg – less than $20,000,
$21,000 – $30,000, $31,000 to $40,000, $41,000 to $50,000, etc. By
doing this, the researcher concludes the characteristics of people
belonging to different income groups
12. Reduce Sample Bias: Using the probability sampling method, the bias in
the sample derived from a population is negligible to non-existent.
Probability sampling leads to higher quality data collection as the
sample appropriately represents the population.
Diverse Population: When the population is vast and diverse, it is
essential to have adequate representation so that the data is not skewed
towards one.
Create an Accurate Sample: Probability sampling helps the researchers
plan and create an accurate sample. This helps to obtain well-defined
data.
13. The non probability method is a sampling method that involves a
collection of feedback based on a researcher or statistician’s sample
selection capabilities and not on a fixed selection process.
In most situations, the output of a survey conducted with a non-
probable sample leads to skewed results, which may not represent the
desired target population.
There are situations such as the preliminary stages of research or cost
constraints for conducting research, where non-probability sampling
will be much more useful than the other type.
14.
15. Convenience Sampling is used because of the researcher’s ease of
carrying it out and getting in touch with the subjects.
Researchers have nearly no authority to select the sample elements, and
it’s purely done based on proximity and not representativeness.
In situations where there are resource limitations such as the initial
stages of research, convenience sampling is used.
For example, startups and NGOs usually conduct convenience sampling
at a mall to distribute leaflets of upcoming events or promotion of a
cause – they do that by standing at the mall entrance and giving out
pamphlets randomly.
16. Judgmental or purposive sampling are formed by the discretion of the
researcher.
Researchers purely consider the purpose of the study, along with the
understanding of the target audience.
For instance, when researchers want to understand the thought
process of people interested in studying for their master’s degree.
The selection criteria will be: “Are you interested in doing your masters
in …?” and those who respond with a “No” are excluded from the
sample.
17. Snowball sampling is a sampling method that researchers apply when
the subjects are difficult to trace.
For example, it will be extremely challenging to survey shelter less
people or illegal immigrants. In such cases, using the snowball theory,
researchers can track a few categories to interview and derive results.
For example, surveys to gather information about HIV Aids. Not many
victims will readily respond to the questions. Still, researchers can
contact people they might know or volunteers associated with the cause
to get in touch with the victims and collect information.
18. It allows the researchers to sample a subgroup that is of great interest
to the study.
If a study aims to investigate a trait or a characteristic of a certain
subgroup, this type of sampling is the ideal technique.
In Quota sampling the selection of members in this sampling technique
happens based on a pre-set standard.
In this case, as a sample is formed based on specific attributes, the
created sample will have the same qualities found in the total
population.
19. Create a hypothesis: Researchers use the non-probability sampling
method to create an assumption when limited to no prior information
is available. This method helps with the immediate return of data and
builds a base for further research.
Exploratory research: Researchers use this sampling technique widely
when conducting qualitative research, pilot studies, or exploratory
research.
Budget and time constraints: The non-probability method when there
are budget and time constraints, and some preliminary data must be
collected. Since the survey design is not rigid, it is easier to pick
respondents at random and have them take the survey
or questionnaire.
20. Probability Sampling Methods
Non-Probability Sampling
Methods
Definition
Probability Sampling is a sampling
technique in which samples from a
larger population are chosen using a
method based on the theory of
probability.
Non-probability sampling is a
sampling technique in which the
researcher selects samples based
on the researcher’s subjective
judgment rather than random
selection.
Alternatively Known as Random sampling method. Non-random sampling method
Population selection The population is selected randomly.
The population is selected
arbitrarily.
Nature The research is conclusive. The research is exploratory.
21. Probability Sampling Methods Non-Probability Sampling Methods
Sample
Since there is a method for deciding the
sample, the population demographics are
conclusively represented.
Since the sampling method is arbitrary,
the population demographics
representation is almost always skewed.
Time Taken
Takes longer to conduct since the research
design defines the selection parameters
before the market research study begins.
This type of sampling method is quick
since neither the sample or selection
criteria of the sample are undefined.
Results
This type of sampling is entirely unbiased
and hence the results are unbiased too and
conclusive.
This type of sampling is entirely biased
and hence the results are biased too,
rendering the research speculative.
Hypothesis
In probability sampling, there is an
underlying hypothesis before the study
begins and the objective of this method is to
prove the hypothesis.
In non-probability sampling, the
hypothesis is derived after conducting
the research study.
22. Sampling bias occurs when some members of a population are
systematically more likely to be selected in a sample others.
There are five important potential sources of bias that should be
considered when selecting a sample, irrespective of the method used.
Any pre-agreed sampling rules are deviated from
People in hard-to-reach groups are omitted
Selected individuals are replaced with others, for example if they are
difficult to contact
There are low response rates
An out-of-date list is used as the sample frame (for example, if it
excludes people who have recently moved to an area)
23. A sampling error occurs when
the sample used in the study
is not representative of the
whole population.
Types of Sampling Error are.
Population specification error
Sample frame error
Selection or Chance error
Response error
24. Increase sample size: A larger sample size results in a more accurate
result because the study gets closer to the actual population size.
Divide the population into groups: Test groups according to their size
in the population instead of a random sample. For example, if people of
a specific demographic make up 20% of the population, make sure that
your study is made up of this variable.
Know your population: Study your population and understand its
demographic mix. Know what demographics use your product and
service and ensure you only target the sample that matters.