Thanks for such a great content and your effort. Would you mind explaining further why you think that mode = median? Since this graph seems like a positively skewed graph, I though mode is around 3, median 4 or 5 and mean between 6 and 10.
Great content. Is non-normal distributions listed separately to put emphasis on it? I believe it will be included within the concept of the overall distributions
You failed to mention bayes theorem and binomial distribution which is used here just as heavily as normal distribution particularly when quantifying the probability distribution of the accuracy of unsupervised learning models. This video is not comprehensive at all
If you thought a video titled “5 concepts in statistics you should know” would be a comprehensive breakdown of literally every stats concept you need for data science, then I have a bridge to sell you.
I would describe that as a positively skewed normal distribution, not an exponential distribution. Also, it's the 68-95-99.7 rule
Nice Webster
Thank you for sharing this excellent video, Dan!
Such a simple and straight forward refresher. I'm grateful for your work
Nice for having a brush up! Thank you!
Great Video! Though CLT wasn't much clear! Thanks!
11:16. I think you have a typo: The Normal distribution should be 68-95-99.7%, not 65-95-99.7%
Hypothesis testing and P value nicely explained, thank you!
Thank you!
significance level is the probability of making type 1 error, which is rejecting null hypothesis when it was true
6:43 should the numerator be cov(X,Y)? Seems there is a 1/(N-1) term missing.
Thanks for the video! I The correlation formula is wrong though, the covariance is the numerator divided by n.
I definitely appreciate the explanation then the applied DS examples right after. Thank you!
That's the best way to learn :)
Thanks for such a great content and your effort. Would you mind explaining further why you think that mode = median? Since this graph seems like a positively skewed graph, I though mode is around 3, median 4 or 5 and mean between 6 and 10.
For the normal distribution, is it 66-95-99.7 rule or 68-95-99.7?
it is 68% within 1 SD. it must be a typo on Dan's end. The graph though does represent it correctly.
@@TheNIK21HIL yeah typo
in #2 at 4.30 mins how he told that mean,median and mode value can anyone explain please
in 3-sigma rule isn't it 68 instead of 65 at first standard deviation?
Could you mention tools used to design and present your slides thanks!!!
I am binge-watching your channel ! 😎
In the correlation section - why not just straight up remove the outliers? 🤔
that's what he is telling with a fancy name, you will use quartiles to confirm which of the points are outliers
could you give me ideas for data science projects that deliver value to businesses
These are crucial concepts. Thanks
If you're using a real world example, you shouldn't "ASSUME" the SD to be something. Can you find out how it's determined in real world?
Also where is the link for Meta Statistical Interview questions video please?
Can you help me understand on what basis have you assumed population standard deviation to be 20?
could you also use Spearman Correlation if you have outliers in your data?
late but yeah u could
2pm - poisson distribution
1:08 8 hours a day in Facebook????? What is the X at the bottom?
Great content. Is non-normal distributions listed separately to put emphasis on it? I believe it will be included within the concept of the overall distributions
You failed to mention bayes theorem and binomial distribution which is used here just as heavily as normal distribution particularly when quantifying the probability distribution of the accuracy of unsupervised learning models. This video is not comprehensive at all
If you thought a video titled “5 concepts in statistics you should know” would be a comprehensive breakdown of literally every stats concept you need for data science, then I have a bridge to sell you.