Brandon the way you present and explain these concepts, you are truly gifted! Your own clarity of concepts and the effort put in to make these dense concepts clear to the viewer are very obvious. Kudos sir!
I've been using your videos to refresh my basic stats for my final dissertation defense in biostatistics. Thank you for these videos, they are fantastic!
Hi Brandon, so there are multiple ways of calculating Z-scores. If the sample is regular Z = x-xbar / standard deviation if it is a sampling distribution: Z = xbar - E(xbar) / (standard_deviation / sqrt(n)) if it is a sampling proportion: Z = pbar-E(pbar)/sqrt(p(1-p)/n) Can someone please explain when to use which one? what is the difference between sampling distribution and sampling proportion? Also how does one come with the formula for standard deviation as sqrt(p(1-p)/n)
Dear Brandon, many thanks for all your fantastic videos! One question: in minute 11.01, when calculating the standard error, the formula demands to put in a value for "p" (population proportion), but instead you fill in the value 0.567, which was previously calculated as a value for "p bar" (sample proportion). Why is that so? Do you consider that "p" and "p-bar" are the same?
i'm gonna assume they're the same for now since he only takes one sample proportion (one test to find E(p-bar)), whereas in previous videos on sample means, Mr. Brandon takes multiple samples (9 test to find E(x-bar)). add a grain of salt to that since this is only my hypothesis
Hello, I've got the same doubt after rewatching the video I've got clarity. It's because population proportion is the expected value of the sample proportions E(p(bar)) = P. And E(p(bar)) is the average of the sample proportions that we take. So here E(p(bar)) = P = avg(all(p(bar))). there is only one p(bar). so P = p(bar)
Hi Brandon, You can create your sampling distribution with only one sample because the rule of the approximation to normal is fine for this example. Am I right? or Can you create sampling distribution with only one sample in general? Thank you in advance.
Sorry, what are these tests you are running at 11:30 ? Before you said n/N and its relationship to 5%. Now you are saying stuff about np and n(1-p) and their relationship to 5%. Whats going on?
@BrandonFoltz -- I have the same question as the OP above. I assume that I'll find out why you are using 5 to determine if you can use the normal distribution in a prior video, but when I see it here in the video, I have no idea where it comes from. The 5% that Ethan mentions I think is just a test of significance and unrelated to the 5 mentioned at 11:30 (I think?).
Hi Brandon, thanks for this wonderful video but I'm a little confused in 10:19, i thought the formula for z-score is "z = (x-μ)/σ," are there different formulas in calculating z-score for standard error for mean and standard error for proportion ?
It's sampling distribution of sampling proportion standard error of mean is as standard deviation of sampling distribution. Maybe that is the reason of using standard error instead of standard deviation of population or sample
Brandon the way you present and explain these concepts, you are truly gifted! Your own clarity of concepts and the effort put in to make these dense concepts clear to the viewer are very obvious. Kudos sir!
Thank you! :)
i am binge-watching your videos for my statistics exam. wish me luck. and thank you for making such helpful and understandable statistics materials.
I've been using your videos to refresh my basic stats for my final dissertation defense in biostatistics. Thank you for these videos, they are fantastic!
Thanks for simplifying stats.Keep enlightening us.
11:18 how we substitute the value of population proportion p with sample proportion p-bar which is 0.567
I am confused too!!
It's a really great video to understand. I believe lots of effort and knowledge is required to create such a type of tutorial. really thanks
Best channel i found... best videos and playlist
Glad you enjoy it!
thank you so much B, it is goign a long way in my python work
Thank you Brandon. You are the best
Brandon you are explaining the concepts very clearly
You are the best sir
Hi Brandon, so there are multiple ways of calculating Z-scores.
If the sample is regular
Z = x-xbar / standard deviation
if it is a sampling distribution:
Z = xbar - E(xbar) / (standard_deviation / sqrt(n))
if it is a sampling proportion:
Z = pbar-E(pbar)/sqrt(p(1-p)/n)
Can someone please explain when to use which one?
what is the difference between sampling distribution and sampling proportion?
Also how does one come with the formula for standard deviation as sqrt(p(1-p)/n)
You literally saved my educational career, thank you.
loved it
Thanks
Dear Brandon, many thanks for all your fantastic videos! One question: in minute 11.01, when calculating the standard error, the formula demands to put in a value for "p" (population proportion), but instead you fill in the value 0.567, which was previously calculated as a value for "p bar" (sample proportion). Why is that so? Do you consider that "p" and "p-bar" are the same?
i'm gonna assume they're the same for now since he only takes one sample proportion (one test to find E(p-bar)), whereas in previous videos on sample means, Mr. Brandon takes multiple samples (9 test to find E(x-bar)). add a grain of salt to that since this is only my hypothesis
Hello, I've got the same doubt after rewatching the video I've got clarity. It's because population proportion is the expected value of the sample proportions E(p(bar)) = P.
And E(p(bar)) is the average of the sample proportions that we take.
So here E(p(bar)) = P = avg(all(p(bar))).
there is only one p(bar).
so P = p(bar)
awesome video! THank you!
"I think we forgot to mention that if the population proportion is known, we would have had to use it."
thank you kindly, this was really helpful...
Hi Brandon, You can create your sampling distribution with only one sample because the rule of the approximation to normal is fine for this example. Am I right? or Can you create sampling distribution with only one sample in general? Thank you in advance.
Sorry, what are these tests you are running at 11:30 ? Before you said n/N and its relationship to 5%. Now you are saying stuff about np and n(1-p) and their relationship to 5%. Whats going on?
@BrandonFoltz -- I have the same question as the OP above. I assume that I'll find out why you are using 5 to determine if you can use the normal distribution in a prior video, but when I see it here in the video, I have no idea where it comes from. The 5% that Ethan mentions I think is just a test of significance and unrelated to the 5 mentioned at 11:30 (I think?).
11:18, In calculating the standard error of proportion we need population proportion then why you are putting value of sample proportion
Okay. So what if the proportion is not normally distributed
Thank you boss!
timestamp 16:43: Why 0.55 is on the left side of 0, since it is a positive number, can’t it be between 0 and 0.6572 ?
Very nice.. Thanks sir
Thank you sir for such a beautiful knowledge 🙏
Do u do statistics plz
@@Ilemaurice687 Yes sir
@@laxmimishra6012 help me plz i will send u questions plzz cant find someone
These people dont even reply which have done videos on RUclips they r not helping
@@laxmimishra6012 plz if u can help me i will sen u some questions will you be able to help me pleaseee
How can we get a relationship when independent variable is qualitative in nature and dependent variable is in quantative
Hello! A few ways, but easiest may be to set up dummy variables for the IVs and then use regression.
is sample proportion & population proportion are same?
14:38 the mean(at z=0) that was used, is that population proportion P ? I am a bit confused.. can some one help me with this?
Hi Brandon, thanks for this wonderful video but I'm a little confused in 10:19, i thought the formula for z-score is "z = (x-μ)/σ," are there different formulas in calculating z-score for standard error for mean and standard error for proportion ?
It's sampling distribution of sampling proportion standard error of mean is as standard deviation of sampling distribution.
Maybe that is the reason of using standard error instead of standard deviation of population or sample
Standard error of mean and standard deviations of sampling distribution are same
Best