agree like some in the comments, that the most helpful part is at 2:55 where you clarify what identically distributed meant. I am in college right now, and this also hadn't jumped to me until I watched your video. It clearly makes a huge difference when further delving into sample averages and variances as to why the results are what they are....Thanks Mate!
Thanks! Using this for SIMIO, a simulation program for... loads of things. Theme Parks, factories, stadiums, hospitals, anything really. Here's me saying SIMIO more so people googling SIMIO get directed to here for SIMIO help.
If i have a hat of 10 names and select three and after each selection I take it out, would that be considered identically distributed still or would I have to throw the pick back into the hat?
Hi. How you go about it depends on the nature of data (time series, cross section, panel). It's a short question that can not be answered in a few words.
The thing is i am working on a mobile nework simulator. The sources of the data are various and quiet complex. I found out some referebces that stated that we can use some tests such as Pearson correlation coeff or Kolmogorov Smirnoff test for Identical distributions and Run tests for idependency. However i think that all these tests are necessary, but not sufficient conditions to proove the iid property
i.i.d is a very strict assumption, but you must have reason. How you go about it depends on the nature of your data - survey? time series? Sounds like you are reading around. Read the methods that are relevant to the nature of your data - time series, cross section.
The most useful part for me was at t=2:55 where you "spelled out" exactly what being identically distributed meant. Thanks
I think he should prepare it more adequately...
agree like some in the comments, that the most helpful part is at 2:55 where you clarify what identically distributed meant. I am in college right now, and this also hadn't jumped to me until I watched your video. It clearly makes a huge difference when further delving into sample averages and variances as to why the results are what they are....Thanks Mate!
Thanks! Using this for SIMIO, a simulation program for... loads of things. Theme Parks, factories, stadiums, hospitals, anything really. Here's me saying SIMIO more so people googling SIMIO get directed to here for SIMIO help.
Sir u make it very clear I don’t know why they over complicated it with rigorous notation that makes no sense to learners
Wow that cleared things up, thanks for the upload!
GREAT!!! the point in independence!!! I propose you make a new one based on this. Short and to the point.
Thank you, your video is really useful to me
If i have a hat of 10 names and select three and after each selection I take it out, would that be considered identically distributed still or would I have to throw the pick back into the hat?
I am confused with the i.i.d. observations vs i.i.d. variables. Are they the same thing or how can I "see" the difference?
same meaning
Thanks! Great video.
2:24 I heared you said 好看. Thought it was worth mentioning.
Did you watch this just after chinese class? or watching chinese drama?! 谢谢
I tried to learn chinese for a couple years. Can't say I'm any good though :-P 你写汉语写的很好。
fantastic explanation..
Cheers
Thankyou
Is there a way to check if some observed variables are iid?
Hi. How you go about it depends on the nature of data (time series, cross section, panel). It's a short question that can not be answered in a few words.
The thing is i am working on a mobile nework simulator. The sources of
the data are various and quiet complex. I found out some referebces that
stated that we can use some tests such as Pearson correlation coeff or
Kolmogorov Smirnoff test for Identical distributions and Run tests for
idependency. However i think that all these tests are necessary, but not
sufficient conditions to proove the iid property
i.i.d is a very strict assumption, but you must have reason. How you go about it depends on the nature of your data - survey? time series? Sounds like you are reading around. Read the methods that are relevant to the nature of your data - time series, cross section.