In case he doesn't make a video about it - a type 2 error is basically when the null hypothesis was accepted even though it is false. It is basically the opposite of type 1 error. Hope this helps.
Please solve this : Suppose you want to test the null hypothesis H0 : miu=100 against the alternative hypothesis H1: miu >100 using, alpha = 0.05, the population in question is normally distributed with mean 96 and standard deviation 12. A random sample of size 42 is used ( i) Sketch the sampling distribution of X assuming that H0 is true. (ii) Find the probability of type II error and power of the test.
The p-value is the probability of a making a type 1 error. Alpha is the criterion we set for our decision to reject the null hypothesis. It's the probability of getting a type 1 error that we're willing to tolerate when we make the decision to reject the null hypothesis.
Nope. The probability of making a type I error is α, which is the level of significance you set for your hypothesis test. The P value, or calculated probability, is the probability of finding the observed, or more extreme, result when the null hypotheses is true.
My understanding is it's because we want to err on the side of caution before assuming an effect is there. We assume a drug has no effect unless we find strong evidence it does - we don't assume a drug *works* off the bat.
Thank you, that makes sense. Also, I just realized that assuming null hypothesis to be true is NOT to assume anything at all. We are just going with the flow here.
In case he doesn't make a video about it - a type 2 error is basically when the null hypothesis was accepted even though it is false. It is basically the opposite of type 1 error. Hope this helps.
Please solve this : Suppose you want to test the null hypothesis H0 : miu=100 against the alternative hypothesis H1: miu >100 using, alpha = 0.05, the population in question is normally distributed with mean 96 and standard deviation 12. A random sample of size 42 is used ( i) Sketch the sampling distribution of X assuming that H0 is true. (ii) Find the probability of type II error and power of the test.
I think you made a type III error :)
The probability of type 1 error is your alpha level = .01,
the .5% is your p-value.
The p-value is the probability of a making a type 1 error. Alpha is the criterion we set for our decision to reject the null hypothesis. It's the probability of getting a type 1 error that we're willing to tolerate when we make the decision to reject the null hypothesis.
Nope. The probability of making a type I error is α, which is the level of significance you set for your hypothesis test.
The P value, or calculated probability, is the probability of finding the observed, or more extreme, result when the null hypotheses is true.
@@johncox3141 I second that!
THANK YOU!!!!!!!!
Could you also talk about 1-alpha ??
Wait, isn't the probability of making a Type I error the same as the alpha-level?
awareness
thank you.
Where can i get the video about type 2 error ???
A small mistake by Sal sir. Please take note of this comment.
P(type 1 error) = alpha = level of significance = which in this case is 1%
both is not an option; reject or Accept one
awareness is accept muscles
thank you !!!!!
Why do we need to assume that null hypothesis to be true at first?
My understanding is it's because we want to err on the side of caution before assuming an effect is there. We assume a drug has no effect unless we find strong evidence it does - we don't assume a drug *works* off the bat.
Thank you, that makes sense. Also, I just realized that assuming null hypothesis to be true is NOT to assume anything at all. We are just going with the flow here.
Exactly - assume the status quo unless you can prove otherwise.
thank you thank you thank you!
Is this course available in PDF, Sal?
this video was made when i was born lol
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@@Kuldeep-ys7iw fo free
False positives represent!
2022 still kicking
Cool
con job more imitation imposter with laser to hustle with. gee, 100% evidence
still confusing ....
MxR brought me here :D
first
THIRD
Very bad explanation Mr. Khan
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Not a good video, seems like he himself is confused
this guy likes to talk to himself...don't you realise Mr khan that you are continuously confused