Margin of error 1 | Inferential statistics | Probability and Statistics | Khan Academy

[@Petekoko]

Thanks alot Khan Academy! My stats teachers shit and you just saved my life.

[@mndlgaming]

the sound fo CTRL+Z 8:45

[@hung89341]

a sample mean (x bar) is calculated from the population, and sampling distribution of sampling mean (mu of x bar) is formed by many sample mean (x bar) which is come from population, am i correct ? is it also same logic for variance?

[@aadityanarayansaxena2544]

I do not understand why you have taken the standard deviation of the sample as standard deviation of population and then divided it by root of n to get standard deviation of sample

[@sherlockholmes882]

Watch his previous videos.

[@OfficialHuMan]

He divided it by root of n to get standard deviation of the MEAN of the sample. It is a little unclear in this video, and will not make sense if you haven't seen the previous videos

[@LM-he7eb]

It’s called standard error I think you’re confusing Variance & SD

[@Bakchodiwalatrader]

EXACTLY, the value 0.5 which we get here is standard deviation of sample, which will be equal to standar deviation of population/root(n) but i also have doubt why he considered the sample sd as population sd.

[@SimplyAndy]

Nice description - Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it!

[@delcapslock100]

Actually he qualifies that statement by saying he is "reasonably confident" that there is a 95% chance that the true mean is in that interval, and he makes the point over and over that this is really a best guess, because we don't know the true standard deviation of the sampling distribution.

[@panagiotisgoulas8539]

The fact that you replace σ with s seems risky to me. For example when you study normal or not normal population and you don't know σ you use the same notation to estimate σ through s but you never use an arithmetic value for s (later in this occasion you go to your t scores and get it done). It's like saying I got a sample and I found this standard deviation so I am gonna use it to solve my problem. With the same logic I found the sample mean so since it estimates the population mean

[@abrahammathew9783]

Hello Sir, If I take A = 1 and B = 0 then mean will get reversed right? In a problem how should I decide whether A = 1 or B =1?

[@YichongMa]

Yeah, I have the same question actually...

[@veganath]

I understood that it was what ever you deem 'success' = 1 & 'fail' = 0

[@rogersyversen3633]

I dont intuitively understand how that formula creates the mean out of two categorical variables. it wholy based on how many B's you get no matter how many A's you get. how can this determine the percentage between the two?

[@judahdsouza9196]

Roger Syversen because there are only two variables. think about it. the absence of A's is directly related to the number of B's.

[@praveenchandrasrivastava6557]

Will not there be a margin of error while estimating the margin of error when sample variance is estimated as population variance?

[@rohitashvaraj8399]

8:22 .. when he talks about sampling distribution of the sample mean. The sample size is 100 as well as the number of samples are also 100, right ? SO each sample has size of 100 and there are 100 such samples .. some one please calrify

[@judahdsouza9196]

Rohitashva Raj only sample size

[@abonady6747]

@@judahdsouza9196 no i think the sample size is 100 and he repeated this survey 100 times .. this explains what he has mentioned in the video 'it's going to have 100 possible values. This can take on 100 different values here. Really anything between 0 and 1. But I'll draw it kind of continuous because it would be hard for me to draw 100 different bars."

[@SuperMunna77]

What's this multiplying by 0 and 1? This looks wrong when calculating mean. Kindly enlighten.

[@idknuttin]

in which video did he explain why we divide by n-1 when finding the variance?

[@GurfatehSinghDhaliwal]

Fourth video of the playlist

[@roseb2105]

so sampling distribution standard deviation is different from sample standard deviation?

[@subramaniyanvg6367]

Hi sal there is a bug in the calculation for variance you are dividing by n-1 you should use formula from prev video" p1(1-p1)/100" because this way of estimating sample variance will fail. It should be like where p1 = 0.43 then 0.43(1-0.43)/100 = 0.002451 not 0.2475

[@peteroludareoladejo5792]

Pls what is the difference between the two standard deviations you calculated

[@Call4meWT]

6:35 shouldn't that be 0.2476?

[@seeknaylover422]

At 5:30, why is the sample variance divided by (n-1) instead of n? In the most recent videos, the standard error for the sample mean was simply divided by n. Is Bernoulli different? Why is it (n-1?

[@dazzlerflower]

In a random sample taken out of a population, we don't know if the sample that we have taken is unfair and so it is more accurate to use (n-1) instead of n. He made a video on that some time ago....

[@HimanshuRenwalsmilingbabes]

@@dazzlerflower Please share the link of the video you are talking about??

[@MixTheMeister]

This question has popped up several times when I've been watching these videos. Why can you say that μx = μ = p I agree that μx would approximate μ = p depentent on the size of the n. Wouldn't rather be μx ≈ μ = p?

[@steinnd7656]

Why the variance of the sample is divided by 100 - 1? And if so, in what of those videos can I find this?

[@praveen7028]

Look for Unbiased Variance....

[@MixTheMeister]

@BreakerByte Thanks, I've actually viewed the entire playlist. The answer dawned on me basically as soon as I answered the question, but thanks anyway. I need to get through the probability playlist as well though

[@anasmanjothi]

Sir, I am very thankful to you and I am watching all your videos. Can you please tell me that from the video mean and variance of bernouli distribution to video margin of error you are taking value 0(zero) for unfavourable and 1 for favourable, sir I dont understand this can you please give me answer....... Thanking you in Anticipation

[@parvanoff1]

Great like always Sal, i was just thinking about what if you post under downloads of the khanacademy home page just the screenshots from Paint of all yours videos. In that way i think we could have a quick preview of all the Info in that lecture and we would not always need to play the whole video when just refreshing the memory ;) . I hope you get it what i mean. You are just great!!! Thanks a lot !

[@oxblood]

He didn't calculate the values but the margin of error is the the difference between the left bound and the right bound divided by two.

[@TheNovanc]

actually your wording is a bit incorrect, you don't say there is a 95% chance that it is in that intervall, you say that you are confident in 95 of 100 times that it is in that intervall - it has nothing to do with chance in a confidence intervall!

[@MikeDolanFliss]

Norwana yes! you're right, and the difference is important.

[@usharagunath23448]

you rock Sal!!!

[@roseb2105]

is the sampling distribution standard deviation used to rep the population standard |?deviation?

[@ilikechess1]

EXCELLENT WORK =)

[@monster_inside_of_me]

Omg tennnnn yearrsss agooo

[@naazkakria5947]

why we divide by 100-1

[@geoffreyschuchardt5350]

isnt it easier to solve for the standard distribution of the proportion rather than the variance. I cant understand why you keep explaining this through the variance and then back solving for the standard divination in order to use the concept practically.

[@dudelikechill]

The calculator made me lol

[@VanillaDazzle]

MORE STATS VIDEOS!!!!!

[@potatofarmer2099]

please update this video with something that isn't rambling garbage. So hard to watch.

[@BarbaraGonzalez-l4v]

Lopez Nancy Taylor Brian Wilson Scott

[@DrINTJ]

Write a script, organize your thoughts, then try again for God's sake. What an annoying video.

[@bodeabbott3261]

what

[@Freenix101]

I don't like how he repeats his words ALL THE TIME! :( Its the only thing that is bad about it but it ruins the video!!!! He repeats every other word!!! Its awful.