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MTH 220 May 21 Open Questions
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AvatarGreg Miller
9:01
Alright.. time to shut it down!
Kasey
9:00
Dr. Miller I'm still here but I do not have anymore questions for now.  Thanks and see you in zoom tomorrow!
cool 1
AvatarGreg Miller
8:41
small and normal is A-OK.. use the t distribution with n-1 df as the sampling distribution and rock and roll like in Case 2A.
cool 1
8:40
That's a nice observation... if asked about testing a mean or doing a CI with a small sample and skewed data.. your response should be "Stop... this isn't appropriate with our methods"
Kasey
8:39
So it is safe to say that we will not see a small sample and skewed data... only small and normal.
AvatarGreg Miller
8:33
Sounds good..
Ashli Owens
8:33
I am going to watch another video, I may or may not be back before it is over. Good night, if I am not.
AvatarGreg Miller
8:28
Kasey... NOW you've got it.. that's how the simulations for each Page 60 picture were done
cool 1
Kasey
8:27
ok gotcha. n 4 is used 10,000 separate times in the simulation to create 10,000 samples of the same size...
Ashli Owens
8:27
Thank you!
AvatarGreg Miller
8:27
The second part about s replacing sigma is true, but not essential to include in the flow of solving the case.
The first sentence of your quote needs to be mentioned.
8:26
Ashli.. the "it" that appears in your quote is "the population"
Ashli Owens
8:25
I am working my way through the case to get prepared for the next video, and I just want to confirm something. When we create the test statistic for 2B, we need to first state that "although it is not normal, it is a large sample size, so we can invoke CLT. Which allows us to state that X-bar is approximately standard normal." Next we need to also state that when n is large s is approximately sigma, there fore the test statistic((X-bar-mu)/(standard deviation/sq. rt. of n)). Is there any other step before beginning the calculation that I am not remembering?
AvatarGreg Miller
8:25
Kasey.. n = 4... but that value of n = 4 is USED 10,000 separate, individual times.. to create 10,000 samples of the SAME size... each of one them contributing an x-bar
Kasey
8:24
so n is 4 or 10,000?
AvatarGreg Miller
8:24
We have 10,000 samples of size 4 from the flat, uniform population.  Each of those samples creates an X-bar.... the histogram represents the plot for those 10,000 X-bars
In the first histogram on Page 60.. upper left:
8:23
No.
Kasey
8:23
100,000 in the second....
8:22
so there is 40,000 samples in the first one?
AvatarGreg Miller
8:17
So, each of those nine histograms is comprised of 10,000 X-bar values.
Then 10,000 samples EACH of size 50
Then 10,000 samples EACH of size 10
8:16
There were 10,000 samples EACH of size 4
Kasey
8:15
On page 59 you talked about using 10,000 values of x being place on a histogram but then you said you only placed 4,10,  and 50 on the histograms on page 60?
AvatarGreg Miller
overall.. skewed right data is slightly more popular to see in applications.. especially the sciences.
8:14
Now, it is very dependent on the scenario.. I mean the 2B data is skewed left... but..
By the way... it is more popular in applications to see "skewed right" data than "skewed left".
8:13
When I was writing that section... I just wanted to use three different shapes.
Kasey
8:13
I had wondered Ashli's second question as well.
AvatarGreg Miller
8:07
"f" and "r" are next to each other on the keyboard
8:06
"mirror image OF what you see"
8:05
Ashli, Question 2:  Good question.. there was no need to include "skewed left" b/c the resulting pictures would have just been the "mirror image" or what you see.. by the time we get to n=50.. mirror image of normal.. is.. well.. normal... so there is nothing to be gained.. it's the same story.. another verse.
cool 2
Ashli Owens
8:04
That is what I thought you meant for the x-bar...thanks!
AvatarGreg Miller
8:03
Ashli, Question 1:  I just mean that the x-bars in the simulation very well COULD have been the actual x-bar we did see... that's all that's meant by that.. they are from the same population.. they are made up from a sample of the same size.. so they COULD have been our X-bar... but weren't.
Ashli Owens
8:02
8:01!
AvatarGreg Miller
8:02
Ok.. nobody here for an hour and then ya'll both pop up.. time for me to wake up.. hold on
Kasey
8:01
It's me.
cool 1
Guest
8:01
Hi Dr. Miller! I'm here but I was just checking out what was being discussed!
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