Wow! I studied biostatistics from UNMC, Nebraska, but couldn't find their teaching as accurate as this video. I actually struggled for the the whole semester if I could understand their concepts.
Is it correct to assume that this is only suitable or commonly used for experiemental research design to find cause and effect? How will this help or how is this relevant in Pearson correlation to study relationship between variables? I'm confused, is the P-value in the video referring to the P in Pearson correlation coefficient?
I have watched many videos of P-value but I am still confused about one thing. How does a smaller P-Value reject the null hypothesis? If all players actually had a height of 177 cm then we would get a smaller P-value, but still our Null Hypothesis should have been true. Can someone please help me out?
I'm not sure if she mentioned it in the video or not but hopefully this comment helps! Basically, the p-value is calculated assuming that the null hypothesis is TRUE. That means that, for this example, we are calculating the probability that our sample has a mean of 1.77m when we are assuming the entire population has a mean of 1.77 as well. This in turn means that our p-value would be 1 because there is a 100% chance that our sample has a mean height of 1.77m or greater when the entire population has a mean of 1.77m. This means that as the mean of our sample gets further away from 1.77m our p-value DECREASES because the chance of obtaining that value when the null hypothesis is true also DECREASES. Eventually, if you gain a value far enough away from 1.77 then the p-value would become so small that the null hypothesis simply couldn't be true. This then means that we can REJECT the null hypothesis because the p-value is so SMALL that it is near impossible to coincidentally gain those values. So for example, your sample has a mean of 3m, the likelihood of this happening when the mean of your population is 1.77 is super unlikely meaning that the p value will be super small. So small in fact that it would be unrealistic to consider the null hypothesis (the population having a mean of 1.77m) true and so we reject it. I hope that answers your question, if not just say and I'll give it another go :)!
It is very kind of you to follow up with me. No, I still do not get it. It is so very much to absorb, understand and, then, put into practice. It just does not cognitively click.@@sumayyahsalem4554
OK, I"m going to watch your example and expect to be informed and pleased with your explanation. But, as an American, the average man here never measures himself in meters and has no idea how tall he is in meters. Just how we roll. It would be better for us to use meters. But we don't.
The way She is explaining.... That's just awesome. I wish to have a teacher like her for all subjects.
Tonns of love from Ormanjhi,Ranchi, Jharkhand.
You don't have idea how much you presented it sweet and soft
Thanks : )
Wonderful!It is so clear to understand!
Thank you !
Wow! I studied biostatistics from UNMC, Nebraska, but couldn't find their teaching as accurate as this video. I actually struggled for the the whole semester if I could understand their concepts.
Here from UNO lol
@@a_aysh Glad to see you. In which year?
You made it so easy. Thank you for the explanation!
Long time no news from your valuable chanel
excellent presentation
Excellent explanation
Glad it was helpful!
Is it correct to assume that this is only suitable or commonly used for experiemental research design to find cause and effect? How will this help or how is this relevant in Pearson correlation to study relationship between variables? I'm confused, is the P-value in the video referring to the P in Pearson correlation coefficient?
Excellent explanation, thank you.
Thank you for this simple explanation 👍👍👍
Your explanation is very good!
Glad it was helpful!
thank you Ma'am... thanks a lot☺☺☺
Very helpful. Thanks.
Glad it was helpful!
Best explanation ❤
Amazing channel. Lots of love❤
Many many thanks!!! Regards Hannah
Thanks for explaining it beautifully 😊
Glad it was helpful! Regards Hannah
I have watched many videos of P-value but I am still confused about one thing. How does a smaller P-Value reject the null hypothesis? If all players actually had a height of 177 cm then we would get a smaller P-value, but still our Null Hypothesis should have been true. Can someone please help me out?
I'm not sure if she mentioned it in the video or not but hopefully this comment helps! Basically, the p-value is calculated assuming that the null hypothesis is TRUE. That means that, for this example, we are calculating the probability that our sample has a mean of 1.77m when we are assuming the entire population has a mean of 1.77 as well. This in turn means that our p-value would be 1 because there is a 100% chance that our sample has a mean height of 1.77m or greater when the entire population has a mean of 1.77m. This means that as the mean of our sample gets further away from 1.77m our p-value DECREASES because the chance of obtaining that value when the null hypothesis is true also DECREASES. Eventually, if you gain a value far enough away from 1.77 then the p-value would become so small that the null hypothesis simply couldn't be true. This then means that we can REJECT the null hypothesis because the p-value is so SMALL that it is near impossible to coincidentally gain those values. So for example, your sample has a mean of 3m, the likelihood of this happening when the mean of your population is 1.77 is super unlikely meaning that the p value will be super small. So small in fact that it would be unrealistic to consider the null hypothesis (the population having a mean of 1.77m) true and so we reject it. I hope that answers your question, if not just say and I'll give it another go :)!
@@theflyingnomad7103 thanks a tonne😃
I was looking at it in a wrong way. Your explanation cleared my doubt completely.
@@akshaysingh7962 I'm glad I could help :)
@theflyingnomad7103 thank you! I have an exam coming up and this has been the best explanation of p value I have ever seen. Thank you!
@@theflyingnomad7103thank youuuuuuuuuuuu
Excellent lesson, thank you!
Is it necessary to calculate p value in t test or we can reject or accept null hypothesis by critical value .
Clearly explained, great video ;)
I understood this until I didn’t.
Do you understand it now
It is very kind of you to follow up with me. No, I still do not get it. It is so very much to absorb, understand and, then, put into practice. It just does not cognitively click.@@sumayyahsalem4554
Very clear!
Glad you think so!
V.good ,continue it the same
Thanks : )
quality video!
Vielen Dank Thomas : ) Ja wir geben uns immer viel Mühe und es wird immer professioneller! Aber auch viel Arbeit : )
Long time no video
OK, I"m going to watch your example and expect to be informed and pleased with your explanation. But, as an American, the average man here never measures himself in meters and has no idea how tall he is in meters. Just how we roll.
It would be better for us to use meters. But we don't.
👍🏻
Unhelpful.
Thanks!
@@datatabYou're welcome.
Anybody who understands better to explain please😢
Long time no news from your valuable chanel