you are the only teacher that really helped me understand what i am learning. all other videos only give me what i need to know at face value, but when you teach........wig ! king of statistics
I am told null and alternative hypothesis are mutually exclusive ,so I think h1: mu not equal to 90,however in some videos and texts I saw your approach. Could you please shed some light on that?
You are correct in that the two are mutually exclusive. The one containing the condition of equality must be the null. The reason we often reduce the null to only the "equal to" is because this is the part of the null assumed true so that we have a sampling distribution with a known mean to use in calculating p-value. For example, if the null initially was "Greater than or equal to 60," we assume Mu EQUALS 60, and use a distribution with 60 as the mean to determine how likely our one sample mean is compared to an assumed mean of 60: our p-value. The "greater than" portion of the null is not important for this reason AND because the only way we will REJECT THE NULL is if we have a sample mean on the extreme left tail, suggesting the mean is less than 60 [the Alternative hypothesis].
you are the only teacher that really helped me understand what i am learning. all other videos only give me what i need to know at face value, but when you teach........wig ! king of statistics
Best explanation in RUclips!
really appreciate this, even my teacher didnt teach me the way you do. hell thanks Mr R.
Thank you, Shay. Glad you liked it.
Thanks, Han Solo... the Force is strong with you!
thanks. Have been making new, much more concise and better material at StatsMrR on the net. You may find it very helpful
Stats with Mr. r thank you!
Thanks, This was super helpful.
You are awesome. Thank you
I am told null and alternative hypothesis are mutually exclusive ,so I think h1: mu not equal to 90,however in some videos and texts I saw your approach. Could you please shed some light on that?
You are correct in that the two are mutually exclusive. The one containing the condition of equality must be the null. The reason we often reduce the null to only the "equal to" is because this is the part of the null assumed true so that we have a sampling distribution with a known mean to use in calculating p-value. For example, if the null initially was "Greater than or equal to 60," we assume Mu EQUALS 60, and use a distribution with 60 as the mean to determine how likely our one sample mean is compared to an assumed mean of 60: our p-value. The "greater than" portion of the null is not important for this reason AND because the only way we will REJECT THE NULL is if we have a sample mean on the extreme left tail, suggesting the mean is less than 60 [the Alternative hypothesis].
AMAZING THANKS!!!!!