Types of Sampling Methods (4.1)
Summary
TLDRThis video script explores various sampling methods for research, emphasizing the importance of unbiased samples. It explains biased samples like convenience and voluntary response samples, which can skew results. The script then introduces three unbiased methods: simple random sampling (SRS), stratified random sampling, and multi-stage sampling. SRS ensures equal chance selection, while stratified sampling divides the population into groups for more representative results. Multi-stage sampling involves multiple SRS steps to obtain a sample. The script also mentions using a random digits table for SRS, providing a practical approach to random selection.
Takeaways
- 📝 The transcript discusses the concept of 'foreign population' and 'sample' in the context of research methodology, emphasizing the importance of unbiased sampling for accurate conclusions.
- 🧐 Biased samples occur when certain parts of the population are favored over others, leading to skewed results. Two types of biased samples mentioned are 'convenience sample' and 'voluntary response sample'.
- 🚶 Convenience sampling is biased because it only includes people who are easy to reach, not giving every member of the population an equal chance to be part of the sample.
- 🗣️ Voluntary response sampling is also biased as it tends to attract individuals with a strong interest in the survey topic, potentially excluding those with less interest.
- 🔍 An unbiased sample, representative of the entire population, ensures that each member has an equal chance of being chosen, which is crucial for the validity of the research.
- 🎯 Three types of unbiased sampling methods are discussed: stratified random sampling, multi-stage sampling, and simple random sampling (SRS).
- 🔄 Simple random sampling (SRS) is the most basic type of unbiased sampling, where each individual has an equal chance of being selected for the survey.
- 📈 Stratified random sampling divides the population into groups (strata) and takes a simple random sample from each, ensuring representation from each group.
- 📊 Multi-stage sampling involves multiple rounds of simple random sampling to reach the final sample, going through different stages to select the sample.
- 📝 The transcript also introduces the use of a 'random digits table' as an alternative method to select samples randomly, ensuring unbiased selection.
- 📑 Labeling each member of the population with a unique number and using the random digits table to pick numbers ensures a fair and unbiased selection process.
Q & A
What is the definition of 'population' in the context of sampling?
-In the context of sampling, 'population' refers to the entire group of individuals or items from which information is sought.
What is a 'sample' and why is it important?
-A 'sample' is a subset of the population that is taken out to examine and draw conclusions about the whole population. It is important because it allows for practical and manageable research without having to survey the entire population.
What are the two types of biased samples mentioned in the script?
-The two types of biased samples mentioned are the convenience sample and the voluntary response sample.
How does a convenience sample introduce bias into a study?
-A convenience sample introduces bias by only including individuals who are easy to reach, thus not giving everyone in the population an equal chance of being part of the sample.
What is a voluntary response sample and how can it lead to bias?
-A voluntary response sample consists of people who have chosen to include themselves in the sample. It leads to bias because those with a strong interest in the survey topic are more likely to respond, while others may not respond at all.
What is an unbiased sample and why is it desirable in research?
-An unbiased sample is one that is representative of the entire population and gives each individual an equal chance of being chosen. It is desirable because it helps ensure that the research findings are more generalizable to the population.
What are the three different types of sampling methods discussed in the script?
-The three different types of sampling methods discussed are stratified random sampling, multi-stage sampling, and simple random sampling.
How is a simple random sample (SRS) conducted?
-A simple random sample (SRS) is conducted by giving each individual in the population an equal chance of being chosen. It can be visualized as putting names into a hat and selecting a certain number at random.
What is stratified random sampling and how does it differ from a simple random sample?
-Stratified random sampling involves dividing the population into groups of similar individuals, called strata, and then taking a simple random sample from each stratum. It differs from a simple random sample by ensuring representation from different subgroups within the population.
What is multi-stage sampling and how does it work?
-Multi-stage sampling is a process that involves using a combination of two or more simple random samples to obtain the final sample. It requires going through different stages, such as selecting a group first and then selecting individuals from that group in subsequent stages.
How can a random digits table be used to assist in simple random sampling?
-A random digits table can be used to assist in simple random sampling by labeling each member of the population with a number and then using the table to randomly select numbers that correspond to the individuals to be included in the sample.
Outlines
🔍 Introduction to Sampling Methods
This paragraph introduces the concept of a 'foreign population' as the group of interest for information gathering and a 'sample' as a subset of this population examined to draw conclusions. It differentiates between biased and unbiased samples, explaining that biased samples occur when certain parts of the population are favored. Two types of biased samples are discussed: the convenience sample, which includes only those who are easy to reach, and the voluntary response sample, consisting of those who choose to participate, often leading to a non-representative sample. The paragraph sets the stage for discussing various unbiased sampling methods, such as stratified random sampling, multi-stage sampling, and simple random sampling, which aim to ensure each member of the population has an equal chance of being selected.
🎲 Simple Random Sampling (SRS)
The second paragraph delves into the concept of simple random sampling (SRS), which is an unbiased method where every individual in the population has an equal opportunity to be selected. It likens SRS to drawing names from a hat, emphasizing the randomness and equal chance of selection. The paragraph provides an example of how to obtain a sample size of six using SRS, illustrating the process with a practical scenario.
📊 Stratified Random Sampling
This paragraph explains stratified random sampling, a method where the population is divided into 'strata' or groups of similar individuals. Within each stratum, a simple random sample is taken, and these samples are combined to form the full sample. The method is highlighted as effective for ensuring representation from each kind of group within the population, using an example of selecting two people from each of three groups to achieve a total sample of six.
🌐 Multi-Stage Sampling
The final paragraph discusses multi-stage sampling, which involves a sequence of simple random samples to obtain the final sample. It describes the process as going through different stages, starting with selecting a group (e.g., Group 1) using SRS, and then within that group, another SRS is conducted to select individuals for the sample. This method is characterized by its stepwise approach to narrowing down the sample from a broader population.
🔢 Utilizing a Random Digits Table
The paragraph concludes with an alternative method for conducting simple random sampling using a random digits table. It outlines the process of labeling each member of the population with a unique number and then using the table to select numbers corresponding to those labels, ensuring a random selection. The example provided demonstrates how to ignore numbers outside the population size and select the appropriate individuals for the sample.
Mindmap
Keywords
💡Foreign population
💡Sample
💡Biased samples
💡Convenience sample
💡Voluntary response sample
💡Unbiased sample
💡Stratified random sampling
💡Multi-stage sampling
💡Simple random sample (SRS)
💡Random digits table
Highlights
Foreign population refers to the group of things we want information about.
A sample is a part of the population taken out to examine and draw conclusions from.
Different methods of obtaining a sample are discussed in the video.
Biased samples occur when one or more parts of the population are favored over others.
Convenience sample and voluntary response sample are the two types of biased samples.
Convenience sampling only includes people who are easy to reach, leading to bias.
Voluntary response sampling is biased as people with strong interest are more likely to respond.
A good sample is representative of the entire population and gives each an equal chance of being chosen.
Stratified random sampling, multi-stage sampling, and simple random sampling are three types of unbiased sampling methods.
Simple random sample (SRS) is unbiased, giving each individual an equal chance of being surveyed.
Stratified random sample divides the population into strata and takes an SRS from each for a full sample.
Multi-stage sampling uses a combination of two or more simple random samples to find the actual sample.
Random digits table can be used for SRS by labeling each member of the population and selecting numbers.
Ignoring numbers that exceed the population size when using the random digits table for sampling.
The importance of ensuring each kind of group is contacted in stratified random sampling.
Multi-stage sampling involves going through different stages of SRS to get the actual sample.
The video demonstrates the practical application of sampling methods in research.
Transcripts
foreign
population refers to the group of things
that we want information about and a
sample refers to part of the population
that we take out to examine and draw
conclusions from
in this video we will be looking at the
different methods of obtaining a sample
but first let's look at the types of
biased samples bias samples occur when
one or more parts of the population are
favored over others
the two types of biased samples include
the convenience sample and the voluntary
response sample a convenient sample only
includes people who are easy to reach if
this is our population and a researcher
comes along to interview people then you
would only talk to the people that are
closer to him to be part of the sample
this is a biased sampling method because
not everyone in the population has an
equal chance of being part of the sample
only people that are of convenience to
the researcher will be interviewed now a
voluntary response sample consists of
people that have chosen to include
themselves in the sample
so the researcher lets people come to
him this is a buy sampling method
because people with a strong interest
for the survey topic are the ones who
are most likely to respond whereas the
people who don't feel as strongly about
the topic may not even care to respond
remember that our good sample is one
that is representative of the entire
population and it gives each thing an
equal chance of being chosen when you
have these conditions you have what is
known as an unbiased sample we will be
looking at three different types
stratified random sampling multi-stage
sampling and simple random sampling
the most basic type of sampling is the
simple random sample also known as an
SRS
since an SRS is unbiased each individual
has an equal chance of being chosen to
be surveyed in other words to be part of
the sample you can think of an SRS as
putting names into a hat and selecting n
of them so if I wanted a sample size of
6 I would select 6 papers and come up to
the randomly chosen people to interview
them
for a stratified random sample we take
the population and we divide it into
something called a strata strata refers
to the groups of similar people within
each stratum we take an SRS and combine
the srs's to get the full sample for
example we could take an SRS of two
people from each group so that we get
the total of six people
a stratified random sample is good for
making sure that whoever is
administering the sample gets in contact
with each kind of group
the last type of sampling is called
multi-stage sampling for multi-stage
sampling we use a combination of two or
more simple random samples
as the name suggests multi-stage
sampling means you have to go through
different stages to find where your
sample comes from
for example if we have three groups
stage one could be selecting which group
will be picked using an SRS
let's say that I picked out Group 1 then
that means I would only look at group 1.
then for stage 2 I would do another SRS
to get the six random people
we go through different stages of simple
random samples to get the actual sample
and this is why this is called
multi-stage sampling
I'd like to point out that instead of
putting names in a hat there's another
way to pick things randomly
we can use something called the random
digits table the random digits table
consists of a long string of random
numbers and it can help us do an SRS to
use it I would first have to label each
member of the population with a number
we have 30 people in this population so
I will label each person from 1 to 30.
notice how I have written 0 1 instead of
just one doing this helps us use the
random digits table
since each label has two digits we will
read the string of numbers two digits at
a time so let's say I want a sample size
of four
we will use the random digits table to
randomly select four people
the first number on the table is 19 so
person 19 will be part of the sample the
second number is 22 so person 22 will be
part of the sample the third number is
39 but our sample size doesn't go up to
39 so we will ignore it
we will also ignore 50 and 34 but we
will keep number five
we will also ignore 75 62 and 87 but we
will keep number 13. as a result these
are the people we would survey
thank you
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