Cluster Sampling
Summary
TLDRThis script explains the concept of cluster sampling in contrast to stratified sampling. The speaker illustrates that in cluster sampling, the population is divided into natural groups or 'clusters', such as people living on different streets. To conduct the survey, simple random sampling (SRS) is used to select a single cluster, in this case, Main Street. The researcher then interviews everyone within the chosen cluster, making the process more efficient and manageable.
Takeaways
- đ Cluster sampling is a sampling technique where the population is divided into groups or clusters.
- đ Unlike stratified sampling, cluster sampling groups individuals based on natural divisions, such as geographical locations.
- đ The example given is of people living on different streets, which are the natural clusters in this context.
- đ In cluster sampling, the researcher uses simple random sampling (SRS) to select a cluster from the population.
- đŻ Once a cluster is chosen using SRS, the researcher interviews all individuals within that cluster.
- đ„ The selection of individuals for the sample is not random; it's based on the cluster that was randomly selected.
- đ The process involves numbering the clusters (e.g., Maple Street as 1, Main Street as 2, 1st Street as 3) and then using SRS to pick a number.
- đ¶ââïž The purpose of cluster sampling is often to save time and resources, making the data collection process more efficient.
- đ It's important to note that every person in the chosen cluster is interviewed, not just a random selection of individuals.
- đ€ The script emphasizes the difference between cluster sampling and stratified sampling, highlighting the method of grouping in each technique.
- đ The script suggests that cluster sampling can be particularly useful when the population is spread over a large area.
Q & A
What is the main difference between cluster sampling and stratified sampling?
-The main difference is that in stratified sampling, the population is divided into subgroups based on certain characteristics, while in cluster sampling, the population is divided into natural groups or clusters, and one or more of these clusters are randomly selected for the study.
What is a cluster in the context of cluster sampling?
-A cluster in cluster sampling refers to a natural grouping of the population. For example, in the script, the clusters are groups of people living on different streets within the same neighborhood.
Why might someone choose cluster sampling over other sampling methods?
-Cluster sampling might be chosen when it is impractical to sample every individual in the population due to time or resource constraints. It allows for a more manageable and efficient sampling process.
How is simple random sampling (SRS) used in the context of cluster sampling?
-In cluster sampling, SRS is used to randomly select the clusters that will be included in the study. For instance, streets are numbered and one is randomly chosen for the interview.
What is the process of selecting a cluster using SRS as described in the script?
-The process involves numbering each cluster (e.g., streets), then using SRS to randomly select a number within the range of cluster numbers, which determines the cluster to be studied.
What is the assumption when interviewing people from the chosen cluster?
-The assumption is that every individual within the chosen cluster is willing to participate in the interview, providing a complete sample from that cluster.
Can cluster sampling be used when the population is homogeneous?
-Cluster sampling is typically used when the population is not homogeneous and there are natural groupings that can be identified and sampled.
How does the script illustrate the efficiency of cluster sampling?
-The script illustrates efficiency by showing how selecting a single street (cluster) can save time and effort compared to interviewing individuals spread across the entire neighborhood.
What are some potential drawbacks of cluster sampling?
-Potential drawbacks include the possibility of increased sampling error if the clusters are not representative of the entire population or if there is a high degree of variability within clusters.
How does the script differentiate between the numbering of individuals and the numbering of clusters?
-The script explains that in cluster sampling, instead of numbering individuals, the clusters themselves are numbered, and one or more of these numbered clusters are selected for the study.
Can you provide an example of a situation where cluster sampling might not be appropriate?
-Cluster sampling might not be appropriate in situations where the clusters are too similar to each other and do not represent the diversity of the entire population, or when the population is too small to form meaningful clusters.
Outlines
đ Understanding Cluster Sampling
This paragraph introduces the concept of cluster sampling, contrasting it with stratified sampling previously discussed. The speaker explains that in cluster sampling, the population is divided into natural groups or 'clusters' based on a common characteristic, such as living on the same street. Unlike stratified sampling, which groups individuals by attributes, cluster sampling focuses on the grouping of individuals within these clusters. The method is chosen to save time and effort in the data collection process, making it more efficient for large populations spread over a wide area.
Mindmap
Keywords
đĄCluster Sampling
đĄStratified Sampling
đĄSimple Random Sampling (SRS)
đĄPopulation
đĄSample
đĄNatural Grouping
đĄInterview Process
đĄEfficiency
đĄRepresentativeness
đĄNumbering
đĄWillingness
Highlights
Introduction to cluster sampling as a distinct method from stratified sampling.
Explanation of stratified sampling with an example of grouping by color.
Description of cluster sampling involving natural groupings within a population.
Illustration of how people are grouped by the streets they live on.
The concept of a 'cluster' defined as a group of people living on the same street.
The practical challenge of interviewing an entire neighborhood efficiently.
Use of Simple Random Sampling (SRS) to select a street for the interview.
Numbering the streets as clusters for the purpose of random selection.
Random selection process using SRS to pick a street number between one and three.
Main Street being chosen as the cluster for the interview through SRS.
The decision to interview all residents of Main Street as the selected cluster.
Assumption that all residents on Main Street would be willing to participate in the interview.
The importance of numbering clusters rather than individuals in cluster sampling.
The efficiency of cluster sampling in reducing the time and effort required for data collection.
Potential limitations of cluster sampling if not all clusters are representative of the population.
The practicality of cluster sampling for large populations spread over wide areas.
The ethical consideration of ensuring all participants' willingness in the interview process.
Transcripts
okay now isn't it time to move on to
cluster sampling cluster sampling gets
confused with stratified sampling a lot
stratified sampling is what we looked at
at the in the previous video if you're
watching these in order if you're not
then you can find the other one you can
hopefully tell the difference between
cluster sampling and stratified I have
my same population and with stratified
sampling we grouped our people by color
we had all of our blue people than our
black people than our red people and we
looked at them and that was stratified
but with cluster sampling we grouped
them in a different way it's a natural
grouping and each one of the groups is
called a cluster so let's say that all
of these people live on the same street
and I'm going around and I'm
interviewing people so these people live
on one street this group of people lived
on another street and this group of
people lived on another street
let's say this one here was Maple Street
and this one here was Main Street and
this group here lived on 1st Street
and all of these streets are in the same
neighborhood but I don't want to go
around the entire neighborhood because
it's going to take me forever so I want
to save some time I want to save my legs
I want to make this interview process a
little bit easier on myself so what I do
is I use SRS once again but this time
I'm going to use SRS to randomly choose
one Street so I put Maple Street Maple
Street gets the number one Main Street
gets the number two and first Street
gets the number three hopefully that
doesn't confuse you that first Street
gets the number three and then I use SRS
once again to choose that randomly
choose a number between one and three
and it just so happens that the number
that comes up is the number two so use
SRS and I choose the number two which
means Main Street is the cluster that
I'm going to interview so I would
interview all of the people that live on
Main Street and hopefully I would be
able to every single person on Main
Street would be willing to do the
interview but I would interview
everybody on Main Street because Main
Street was the cluster that got chosen
using simple random sampling so instead
of randomly numb instead of numbering
the people in my population I number the
clusters in my population that's the big
difference and I interview everybody
within a particular cluster
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