Відео

fantastic, please how can I contact you?

Let’s go

May I ask, at 4.07 when you found the equation for beta-hat how where did those "n" come from. Thanks

Could you please help me we can calculate the mean rank for more than two groups for WSRT as I found it in some research articles. Thank you in advance.

Hi Sir , Is this linear regression can be useful in analysing stock prices? Is the simple moving average formula (SMA= A1+A2+..An/n) where: An=the price of an asset at periodn n=the number of total periods​ Is this formula resembels the linear regression?

When you fall asleep in math class and wakes up in the middle of a new chapter.

Please suggest me the book to read.

Thank you Dr McCarter for simplifying SEM. I love the way you went through the steps before using SAS. I'm more confident now with solving a CFA.

Here before the fame on gang 🔥💯

Thank you for doing this! Too bad you’re not in Kansas, because there’s not a cloud in the sky at the moment. 🥴🙃

I'm getting an error that says "expecting a name" with this syntax. Do you know what may be the issue? Thanks!

Hi Dr.McCarter, thanks for the video, this really helps! Do you have to use a covariance matrix to call in the data for CFA?

Now this is epic

why n-2 not n-1 for SSE?

Merry Christmas and a Happy New Year to everyone!!!

I have some questions I'd like to ask the experts. 1. I read some articles about methods for handling longitude data, like The SEM approach to longitude data analysis using Calis procedure by An and Yung, but they didn't use path analysis. If I want to use path analysis to analyze longitude data, how should I go about it?" 2.Additionally, my variables include both binary and continuous types. How should I handle this? I find some way that use METHOD=ML to deal with it, is that correct? Basically, I think the outcome should be a little bit like Logistic Regression. Bottom part is my code, but this is not longitude data, and I have no idea that this way can deal with binary variables (TNT and HF is binary). For short the parts, I delete some similar code. proc calis covariance outmodel=_eqparms_ method = MLM ; lineqs TNT = pTNTDM DM +pTNTLVEF LVEF+e_TNT, HF=pHFTNT TNT +pHFbmi bmi+pHFDM DM+e_HF; var TnT tempme bmi dm age lvef egfr msbp edvi_di HF; run; proc print data=_eqparms_; run;

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That was awesome! i am working on memorizing Scripture as well and this was an encouragement to me. Thank you brother :)

Thanks for posting. Difficult to find good explanations on this topic.

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Typo Alert: I have a typo at the bottom of the next to the last slide, where I am talking about the Mean Square Regression (MSR) and its expected value. The last sentence says "MSE is an unbiased estimator of...," but it should be "MSR is an unbiased estimator of..." instead (also, at 18:58 I say MSE instead of MSR). You probably caught this typo and mis-statement, but I wanted to alert it to you anyway, just in case. Sorry for any confusion this may have caused! Thanks for watching! If you found this video informative, please let me know by pressing the like button above and posting a comment below. If you would like to be notified of future videos, press the subscribe button so that you will be notified whenever I post new content. Links to other videos in this series are included below: Next lecture in this series: ua-cam.com/video/SEOl2npRo2Y/v-deo.html Previous lecture in this series: ua-cam.com/video/y-nh8H6PK4g/v-deo.html First lecture in this series: ua-cam.com/video/v4FdcoCUOPA/v-deo.html "A Course on Linear Regression" playlist: ua-cam.com/play/PLyq-3DNuZLa1uE2i1KQEWhPvElSN5aFvW.html