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May 4, 2020 at 4:35 pm
Hi there! why i dont see the Big Data lecture?
May 9, 2020 at 2:31 am
the exact question i wanted to ask?
John Moffat says
May 9, 2020 at 8:21 am
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.
March 12, 2020 at 11:22 am
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.
March 3, 2020 at 8:52 am
wonderful lecturer thanks you teacher.
February 22, 2020 at 10:39 pm
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.
March 12, 2020 at 11:56 am
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.
January 16, 2020 at 4:40 pm
Hi There, do you cover the Big Data topic?
November 11, 2019 at 12:01 pm
Wonderful lectures. keep up with the spirit
November 11, 2019 at 12:09 pm
Thank you for your comment 🙂
October 5, 2019 at 3:07 am
Can you kindly explain Multistage and Cluster sampling more vividly I’m still not getting it, other than that the video is indeed helpful.
October 21, 2019 at 8:50 pm
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.
May 20, 2019 at 1:36 pm
Explained alot. Thnks!
October 26, 2019 at 9:15 am
Wow these videos are actually much easier to understand than the lectures I’m attending to. Thanks
October 26, 2019 at 9:24 am
February 20, 2019 at 6:15 am
February 20, 2019 at 8:05 am
Thank you for the comment 🙂
February 5, 2019 at 9:58 am
February 5, 2019 at 11:40 am
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