This document discusses sampling techniques and sample types. It defines key terms like population, sample, sampling frame, and target population. It outlines the main stages in sample selection and describes four common probability sampling techniques: random sampling, stratified random sampling, cluster sampling, and systematic sampling. It provides examples of how each technique is implemented. The document also discusses non-probability sampling techniques like convenience sampling, purposive sampling, and quota sampling along with their disadvantages.
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.
The process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected
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.
The process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected
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
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
Research is “a process of systematic investigation, development, testing and evaluation of a product to develop or contribute to generalizable knowledge, to the benefit/betterment of the society to resolve problems and to bring intellectual satisfaction”.
This includes carefully planning a study as well as debriefing subjects upon completion of a project.
Basic Terminologies
Population
Sample and Sampling
Advantages & Disadvantages of Sampling
Probability Sampling
Types of Probability sampling
Non-Probability Sampling
Types of Non-probability sampling
The paper discusses how to select representative samples and parameters for deciding sampling techniques. It also adopts a more friendly approach to the determination of samples for population parameters by adopting the use of sample size calculator
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
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
Research is “a process of systematic investigation, development, testing and evaluation of a product to develop or contribute to generalizable knowledge, to the benefit/betterment of the society to resolve problems and to bring intellectual satisfaction”.
This includes carefully planning a study as well as debriefing subjects upon completion of a project.
Basic Terminologies
Population
Sample and Sampling
Advantages & Disadvantages of Sampling
Probability Sampling
Types of Probability sampling
Non-Probability Sampling
Types of Non-probability sampling
The paper discusses how to select representative samples and parameters for deciding sampling techniques. It also adopts a more friendly approach to the determination of samples for population parameters by adopting the use of sample size calculator
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
2. If the method of sample selection was successful, statistics such as
median and range should have similar values for both the sample
and the population.
4. To gather data about the population in
order to make an inference that can be
generalized to the population
5. A biased sample is one in which the data has
been unfairly influenced by the collection
process and is not truly representative of the
whole population.
6. Outlines
Sample definition
Purpose of sampling
Stages in the selection of a sample
Types of sampling in quantitative researches
Types of sampling in qualitative researches
Ethical Considerations in Data Collection
7. 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
مجمو أو فرديين أعضاء الختيار أسلوب هو العينات أخذ
عة
وتق منهم إحصائية استنتاجات لعمل السكان من فرعية
دير
بأكمله المجتمع خصائص
8. A sample is “a smaller (but hopefully
representative) collection of units from a
population used to determine truths about that
population” (Field, 2005)
The sampling frame
A list of all elements or other units containing the
elements in a population.
8
10. Target population
A set of elements larger than or different
from the population sampled and to which
the researcher would
like to generalize
study findings.
11. To gather data about the population in order
to make an inference that can be generalized
to the population
12. Define the target population
Select a sampling frame
Conduct fieldwork
Determine if a probability or nonprobability
sampling method will be chosen
Plan procedure for selecting
sampling units
Determine sample size
Select actual sampling units
Stages in the
Selection
of a Sample
14. Known as probability sampling
Best method to achieve a representative
sample
Four techniques
1. Random
2. Stratified random
3. Cluster
4. Systematic
15. 1. Random sampling
Selecting subjects so that all members of a population have an
equal and independent chance of being selected
Advantages
1. Easy to conduct
2. High probability of achieving a representative sample
3. Meets assumptions of many statistical procedures
Disadvantages
1. Identification of all members of the population can be
difficult
2. Contacting all members of the sample can be difficult
16. Random sampling (continued)
◦ Selection process
Identify and define the population
Determine the desired sample size
List all members of the population
Assign all members on the list a consecutive number
Select an arbitrary starting point from a table of
random numbers and read the appropriate number of
digits
17. 2. Stratified random sampling
◦ The population is divided into two or
more groups called strata, according to
some criterion, such as geographic
location, grade level, age, or income,
and subsamples are randomly selected
from each strata.
18. Stratified random sampling (continued)
◦ Advantages
More accurate sample
Can be used for both proportional and non-
proportional samples
Representation of subgroups in the sample
◦ Disadvantages
Identification of all members of the population can
be difficult
Identifying members of all subgroups can be
difficult
19. Stratified random sampling (continued)
◦ Selection process
Identify and define the population
Determine the desired sample size
Identify the variable and subgroups (i.e., strata) for
which you want to guarantee appropriate
representation
Classify all members of the population as members
of one of the identified subgroups
20.
21. 3. Cluster sampling
The process of randomly selecting intact groups, not
individuals, within the defined population sharing similar
characteristics
Clusters are locations within which an intact group of
members of the population can be found
Examples
Neighborhoods
School districts
Schools
Classrooms
22. Cluster sampling (continued)
◦ Advantages
Very useful when populations are large and spread over a
large geographic region
Convenient and expedient
Do not need the names of everyone in the population
◦ Disadvantages
Representation is likely to become an issue
23. Cluster sampling (continued)
◦ Selection process
Identify and define the population
Determine the desired sample size
Identify and define a logical cluster
List all clusters that make up the population of
clusters
Estimate the average number of population members
per cluster
Determine the number of clusters needed by dividing
the sample size by the estimated size of a cluster
Randomly select the needed numbers of clusters
Include in the study all individuals in each selected
cluster
24.
25. 4. Systematic sampling
◦ Selecting every Kth subject from a list of the
members of the population
◦ Advantage
Very easily done
◦ Disadvantages
subgroups
Some members of the population don’t have an equal
chance of being included
26. Systematic sampling (continued)
◦ Selection process
Identify and define the population
Determine the desired sample size
Obtain a list of the population
Determine what K is equal to by dividing the size of
the population by the desired sample size
Start at some random place in the population list
Take every Kth individual on the list
27. Example, to select a sample of 25 dorm rooms in your
college dorm, makes a list of all the room numbers in the
dorm. For example there are 100 rooms, divide the total
number of rooms (100) by the number of rooms you want
in the sample (25). The answer is 4. This means that you
are going to select every fourth dorm room from the list.
First of all, we have to determine the random starting
point. This step can be done by picking any point on the
table of random numbers, and read across or down until
you come to a number between 1 and 4. This is your
random starting point. For instance, your random starting
point is "3". This means you select dorm room 3 as your
first room, and then every fourth room down the list (3, 7,
11, 15, 19, etc.) until you have 25 rooms selected.
28. According to Uma Sekaran in Research Method for
Business 4th Edition, Roscoe (1975) proposed the rules of
thumb for determining sample size where sample size
larger than 30 and less than 500 are appropriate for most
research, and the minimum size of sample should be 30%
of the population.
The size of the sample depends on a number of factors and
the researchers have to give the statistically information
before they can get an answer. For example, these
information like (confidence level, standard deviation,
margin of error and population size) to determine the
sample size.
33. 2. Purposive sampling:
the process whereby the researcher selects a
sample based on experience or knowledge of
the group to be sampled
…called “judgment” sampling