Відео

Thank You, you helped me understand.

Dear Professor, thanks for the clear explanation!

Good❤

But, we can't say anything about the independence b/w two random variables provided the Covariance between them is zero, right? Then how is 4th property working? Can you clarify please.

Is it possible for a PDF copy of the lecture

Best teacher

👍👍👍

Thank you!

After finding so many videos over the topic my research ends here...

❤❤❤good

❤very good

Analogy with bivariate is shown very elegantly. Thanks.

Important concepts, clear explained! thanks

Is there a way to derive the marginal pdf of each component X_i without resorting to the moment generating function?

Great video. Thank you!

Mr Baker's teaching is very well and clear! And am I the only one who thinks he looks and sounds like Woody from Toy Story?

This is good, thanks for uploading

Thanks!

Thank you!

How large should be the area considered for the analysis? 10 x 10 km? 100 x 100 km?

Very great classes!

thank you!

Thank you, Dr. Baker. Great points..

why my professor is not you.

Thank you for the great presentation. I just ordered the book from Aamazon.

Thank you! That was very good

Hello Sir, Can you please tell what plotting tools and font and line width specifications do you use for your figures? They look really elegant. I would certainly like to replicate the same in my presentations. I usually have problems when i import images to the latex environment and am forced to rescale the image to fit the document appropriately. Looking forward to hearing from you. Thanks. 😊

Thank you Mr. Baker, the video was very useful to me, greetings from Lima, Peru

very clear explanation! thanks

Nice suggestions, Prof. Baker. Which software do you suggest to use for making plots/graphics?

Excellent video... Really helped me to understand the concepts in depth... Thank you Prof.Baker. - Reena,India

Thank you, professor. Can you make a video on how to calculate weights for GMPEs used in PSHA with example. It will be very helpful.

Clear explanation. Thank you.

Thank you Professor for uploading these lectures! They have been of great help to me.

Thank you! Concepts are very well-explained!

Excuse me, sir. Thank you for the video. But I don’t understand yet. Can you please give us an example about how to find variance and covariance of random vector, if expected values is real number?

Thank you

Thank you Sir

How can we get for n random x values in one data set , n mean values? I mean if I have a data set with Gaussian shape, shouldn't have only one mean and sigma. Bu the way, I have a histogram showing counts per channel up to 1024 channels for instance. The example you gave at the minute of 13.14, how would you construct it if you had one mean and one sigma but a vector of random variables as in my example I tried to explain above? (instead of having the mean and Sigma matrices) Actually, in that exmple at the minute of 15.00, you decided to change x matrix having x1 and x1 variables to x (underlined matrix with x1 vector and x2 vector . That confused everything.

How do you call x, mu and sigma in likelihood function of a Gaussian distribution in statistics or in math (Variable, domain, data, parameter in univariate, bivariate, and multivariate case seperately) ? I am also asking this when there is only one data point or when you have a data set of x, when you have a vector of mean and sigmas, so on , so forth. Thanks in advance.

Hi! Prof. Baker, the videos are really helpful! Thank you so much from Canada, Can you please upload such videos covering other chapters of the book (Seismic Hazard and Risk Analysis)?. They boost the comprehension and motivate to go through the book in a more detailed and systematic manner.

Could you do an example of DSHA as well. Thank you.

Could you an example of DSHA as well

𝕡𝐫ｏ𝕄ｏ𝔰𝓶

Thank you for this! My doctoral thesis is in this area! These videos are of invaluable help. Greetings from Chile, the land of earthquakes :)

Excellent video, greetings from Arequipa-Peru

Thanks. Btw, there is a typo: 0.16 should be 0.016 in the example.

It í very useful and compressive explanation professor Baker

Dear professor Thanks for perfect videos. But when you derived the complex response frequency function in terms of c and d, the zeta is missed (around 16 min of video) although the the final function at next slide is correct.

Thanks for your useful videos.