What is difference between quota sampling and stratified sampling, im confused with 60:40 example both sampling methods ?? Or that the other is random and other non random ??
J
John MoffatTutor·
They are similar, but let me give you an example of the two.
Suppose 60% of the population are women and 40% are men, and that we want a sample of 100 people.
With stratified sampling we separate out the women and choose 60 of them at random, then we separate out the men and choose 40 of them at random.
With quote sampling we stop people in the street (whether men or women) but as soon as we have asked 60 women we only then ask men (until we have 40 of them).
A
Allison·
Hi, I want to ask what are the differences between cluster sampling and stratified sampling
M
mrjonbainModerator·
Stratified sampling involves splitting the population into various strata and taking the sample from members of each of the strata. The strata may often be age, gender or some other demographic. Cluster involves splitting the population into various groups and selecting the sample from the whole of some selected groups. For example, selecting various streets within a town's population.
J
Jith·
sir can you explain cluster sampling with the help of another example
S
Sohaib·
can you explain "quasi-random" in simple term?
J
John MoffatTutor·
Only partly random. Not completely ransom.
M
Mannan·
how are cluster sampling and quota sampling used for predicting the results of election in a country?
M
Mannan·
if we conduct a survey by sending a list of questions to our target customers, then the data collected from them (the responses that the target audience sent) is internal data or external data?
R
Raniya·
Where can i find the tests related to every chapter which was informed to us in the end of the video?
J
John MoffatTutor·
They are linked from the main Paper MA page: https://opentuition.com/acca/ma/
M
Mario Wong·
I don’t see lectures for FMA?
J
John MoffatTutor·
Paper FMA is the same exam as Paper MA.
B
Basil Ahmed·
Hello Sir
First of all I would like to thank you for your selfless and generous efforts. Your notes and lectures are brief and to the point.
Recently, I heard that ACCA has made some changes to the MA syllabus. So My question is up to when are these lectures valid,
Can we use this lectures if we are planning to sit MA exam on 2022?
M
Mahrukh·
same question
J
John MoffatTutor·
The only changes for the exams from September onwards are the clarification of two small bits of wording. They do not affect the notes are the lectures and they are valid for all exams up to June 2023.
(This kind of question should be asked in the Ask the Tutor Forum rather than a comment on a lecture. I do not always see comments here, but I always answer questions in the Ask the Tutor Forum within 24 hours.)
R
rumeisa·
hi can we pass the exam with these lectures and notes only?
J
John MoffatTutor·
The notes and lectures cover everything needed to pass the exam well. However it is vital that you buy a Revision Kit from one of the ACCA Approved examiners. They are full of exam standard questions for practice, and practice is essential to passing the exam.
C
Caroline·
Thank you for the lecture but you left out big data or later chapters or?
J
John MoffatTutor·
A lecture on Big Data will be recorded when I have the time. However there are no calculations involved and the notes on it should make sense without a lecture :-)
A
Afag·
your lectures are really awesome. With your lectures i pass f3 with 71%. I hope f2 will be successful too. Many thanks.
J
John MoffatTutor·
Thank you for your comment :-)
I
Ibrahim·
Hello! I am having difficulty understanding the difference between cluster and multistage sampling methods. What is the technical difference here?
M
Mike·
Hi Zeupiter,
Multi-stage sampling: All the samples are taken randomly - let's say there are 20 counties in a country. Select 5 randomly. Then Select 5 cities randomly in those 5 counties, then select 3 streets randomly in each city, then select 5 houses on each street randomly, and ring the bell to survey people who live there.
With Cluster, only the last stage is different: select every house on those streets and survey all of them (every single house on the street - the last step is not-random)
I am preparing for MA, email me if you are looking for a study buddy. [email protected]
S
Segun·
Wow this amazing God bless this platform
J
John MoffatTutor·
:-)
F
Fikeoluwa·
I don't really understand how cluster is not random if out of 100 offices a random sample of 5 offices were chosen. Could you give another example to explain better
A
Asif·
Greetings sir,
Why would we only consider random sampling to have a sampling frame (considering the entire population) ? Could you please elaborate on this concept ? Do you mean by it that we give every individual an equal chance to be selected, and therefore everyone is fitted within the frame of selection, and hence the “sampling frame”. And therefore other sampling methods’ population cannot be given the title of “sampling frame”. Please confirm or correct elaborately if possible.
A
Asif·
Do you mean by it that we give every individual in the population an equal chance to be sampled, and therefore the population is called the sampling frame. Otherwise if it was just about the necessity of having knowledge of each item in the population, then the population of Stratified sampling for instance should also qualify being called as a “sampling frame”.
J
John MoffatTutor·
There is no need for a lecture - what is written in the free lecture notes is all that is needed for the exam (there is not much point in me just reading it out when you can read it yourself :-) ).
If you are not clear about what is written then ask in the Ask the Tutor Forum and I will explain the bit that you are not clear about.
S
Sokhom·
Hi there! why i dont see the Big Data lecture?
L
Lokesh·
Thanks a lot, Your act is very selfless, generous and kind. You are helping thousands of student who can't afford the costly books published by theBPP/KAPLAN. You are the only hope of those people. You are the short cut for people who don't want to go through the 600 pages of Kaplan or 400 pages of Bpp or stuck at somewhere.
I appreciate your Such a selfless and kindful act.
What I think about you Sir, is that, you are one of those sent directly by God.
Once again thank you sir . you lectures are awesome.
A
abdimahad·
wonderful lecturer thanks you teacher.
S
Scott·
Hi.
Thank you for the wonderful lectures.
I may be being silly, but I'm a little confused by the difference between stratified sampling and quota sampling.
The course notes explain that:
Stratified:
If the population was 60% women, 40% men, then 60% of the sample should be women and 40% men.
Quota:
Population is 60% women and 40% men. We want to question a sample of 200. Decide on a quota of 120 women (60%) and 80 men(40%), and stop people as they appear until we have the required number.
The only difference I see is the way in which candidates are chosen (one by one until the quota is satisfied), however, in stratified sampling, it makes no reference to how the 60% and respective 40% are selected.
Any help would be greatly appreciated.
Best,
Scott
L
Lokesh·
I think - In Stratified sampling - The composition/categorisation Sampling should be equal to the composition/categorisation of whole population.
e.g real populayion using the product is 60% women and 40 % men , then it doesn't matter how much sample we take. its just whatever Qty of sample we take should have same composition ( like sample also should be 60 % women and 40% men )
while quata in sampling - They just keep doing sampling till they get the quata fullfilled.
Also, one thing to notice Quata is Not random at all , as we are not ramdomly selecting from the quota e.g we aren't selecting 120 women randomly from 60 % of total women from a list - the original example )
while in stratified sampling which is quasi random . because we select randomly from 60 percent of women.
R
ritaporter·
Hi There, do you cover the Big Data topic?
B
brian·
Wonderful lectures.
keep up with the spirit
J
John MoffatTutor·
Thank you for your comment :-)
K
kodi1122·
Can you kindly explain Multistage and Cluster sampling more vividly I'm still not getting it, other than that the video is indeed helpful.
H
hma1989·
Say you are a business owner and you have 100 offices and each office has 100 employees. You need a random sample of employees.
Multi Stage: Select 5 offices at random and from each office you select 20 employees at random. So total So sample is 100 employees from 5 different offices.
Cluster: Select 5 offices at random and then use every single employee from those offices as your sample.
D
Darin·
Explained alot. Thnks!
A
anasci83·
Wow these videos are actually much easier to understand than the lectures I'm attending to. Thanks
Suppose 60% of the population are women and 40% are men, and that we want a sample of 100 people.
With stratified sampling we separate out the women and choose 60 of them at random, then we separate out the men and choose 40 of them at random.
With quote sampling we stop people in the street (whether men or women) but as soon as we have asked 60 women we only then ask men (until we have 40 of them).
First of all I would like to thank you for your selfless and generous efforts. Your notes and lectures are brief and to the point.
Recently, I heard that ACCA has made some changes to the MA syllabus. So My question is up to when are these lectures valid,
Can we use this lectures if we are planning to sit MA exam on 2022?
(This kind of question should be asked in the Ask the Tutor Forum rather than a comment on a lecture. I do not always see comments here, but I always answer questions in the Ask the Tutor Forum within 24 hours.)
Multi-stage sampling: All the samples are taken randomly - let's say there are 20 counties in a country. Select 5 randomly. Then Select 5 cities randomly in those 5 counties, then select 3 streets randomly in each city, then select 5 houses on each street randomly, and ring the bell to survey people who live there.
With Cluster, only the last stage is different: select every house on those streets and survey all of them (every single house on the street - the last step is not-random)
I am preparing for MA, email me if you are looking for a study buddy. [email protected]
Why would we only consider random sampling to have a sampling frame (considering the entire population) ? Could you please elaborate on this concept ? Do you mean by it that we give every individual an equal chance to be selected, and therefore everyone is fitted within the frame of selection, and hence the “sampling frame”. And therefore other sampling methods’ population cannot be given the title of “sampling frame”. Please confirm or correct elaborately if possible.
If you are not clear about what is written then ask in the Ask the Tutor Forum and I will explain the bit that you are not clear about.
I appreciate your Such a selfless and kindful act.
What I think about you Sir, is that, you are one of those sent directly by God.
Once again thank you sir . you lectures are awesome.
Thank you for the wonderful lectures.
I may be being silly, but I'm a little confused by the difference between stratified sampling and quota sampling.
The course notes explain that:
Stratified:
If the population was 60% women, 40% men, then 60% of the sample should be women and 40% men.
Quota:
Population is 60% women and 40% men. We want to question a sample of 200. Decide on a quota of 120 women (60%) and 80 men(40%), and stop people as they appear until we have the required number.
The only difference I see is the way in which candidates are chosen (one by one until the quota is satisfied), however, in stratified sampling, it makes no reference to how the 60% and respective 40% are selected.
Any help would be greatly appreciated.
Best,
Scott
e.g real populayion using the product is 60% women and 40 % men , then it doesn't matter how much sample we take. its just whatever Qty of sample we take should have same composition ( like sample also should be 60 % women and 40% men )
while quata in sampling - They just keep doing sampling till they get the quata fullfilled.
Also, one thing to notice Quata is Not random at all , as we are not ramdomly selecting from the quota e.g we aren't selecting 120 women randomly from 60 % of total women from a list - the original example )
while in stratified sampling which is quasi random . because we select randomly from 60 percent of women.
keep up with the spirit
Multi Stage: Select 5 offices at random and from each office you select 20 employees at random. So total So sample is 100 employees from 5 different offices.
Cluster: Select 5 offices at random and then use every single employee from those offices as your sample.