Types of Sampling Methods (4.1)

Summary

This 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

00:00

🔍 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.

Keywords

💡Foreign population

The term 'foreign population' refers to the entire group of individuals or items that a researcher is interested in studying. In the context of the video, it is the total group from which a sample is to be drawn for analysis. The script mentions that a sample is taken from this population to examine and draw conclusions, emphasizing the importance of the foreign population as the basis for any sampling method discussed in the video.

💡Sample

A 'sample' is a subset of the foreign population that is selected for study to represent the larger group. The video script explains that conclusions about the entire population are drawn from this smaller group. The concept is central to the video's theme, as different sampling methods are explored, each aiming to select a sample that accurately represents the foreign population.

💡Biased samples

Biased samples occur when the sampling method favors certain parts of the population over others, leading to potential inaccuracies in the study's results. The video script discusses two types of biased samples: convenience samples and voluntary response samples. These are important to understand because they can skew the results and are contrasted with unbiased sampling methods later in the video.

💡Convenience sample

A 'convenience sample' is a type of biased sample where only individuals who are easily accessible to the researcher are included. The video provides an example of a researcher interviewing only those people who are close to them, which does not give everyone in the population an equal chance of being part of the sample, thus introducing bias.

💡Voluntary response sample

A 'voluntary response sample' consists of individuals who choose to participate in the study. The video script points out that this method is biased because those with a strong interest in the survey topic are more likely to respond, while others may not, which can lead to a non-representative sample.

💡Unbiased sample

An 'unbiased sample' is one that is representative of the entire population, with each member having an equal chance of being selected. The video script emphasizes the importance of an unbiased sample for accurate research findings. It serves as a benchmark against which other sampling methods are evaluated in the video.

💡Stratified random sampling

Stratified random sampling is a method where the population is divided into subgroups, or 'strata', that share similar characteristics. The video script explains that a simple random sample (SRS) is then taken from each stratum and combined to form the full sample. This method ensures representation from each group within the population.

💡Multi-stage sampling

Multi-stage sampling involves using multiple rounds of simple random samples to obtain the final sample. The video script describes it as a process where different stages are used to narrow down the selection, such as first choosing a group and then selecting individuals from that group, making it a more complex but potentially more targeted sampling method.

💡Simple random sample (SRS)

A 'simple random sample', also known as SRS, is the most basic form of sampling where each individual has an equal chance of being chosen. The video script uses the analogy of drawing names from a hat to illustrate this method, emphasizing its unbiased nature and its role as a fundamental concept in sampling.

💡Random digits table

A 'random digits table' is a tool used to assist in selecting a simple random sample. The video script explains how it can be used by labeling each member of the population with a number and then using the table to select numbers corresponding to those labels, providing a systematic approach to achieving randomness in sampling.

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