Statistics 101: Descriptive Statistics, IQR and Box Plots
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- Опубликовано: 30 июл 2024
- Box plots, also known as box and whisker plots, are one of the first visual tools available for exploratory data analysis. Box plots allow us to see the shape of our data, and the variability of our observations, and make comparisons among different groups or measures easy to interpret. All you need are a few measures and the interquartile range or IQR. Thanks for watching!
My playlist table of contents, Video Companion Guide PDF documents, and file downloads can be found on my website: www.bcfoltz.com
#statistics #regression #machinelearning
Amazing playlists. I am going through each one of them one by one. I suggest you should also make a playlist for Machine Learning! It would be really helpful for upcoming Data Scientists. :)
I'm from Brazil and I just want to thank you for helping me to learn Statistics!
This is the best explanation of interpreting Box plots I have come across. Thank you so much for the simple descriptions and that last comparison helped appreciate their wide use in research. Thanks a lot!
you are good teacher ever. I have attained all of you tutor till part 18.
Excellent video!
Really appreciate your content. Thank you so much, please keep making it!!
God Bless You Sir!
I aim to study all your stat videos within this february. Thank you so much Brandon!
Brandon You are simply amazing. You explained thing in very easy way
a little fast for this beginner but once i discovered the pause button i learned a lot!! thank you for teaching
Very helpful information!
I could see how having a box plot can easily help you identify data and issues that need immediate attention.
Subscribed.... Great stuff of playlist.. So i am yet to start from thr beginning... Awesome work.. Thanks for all ur efforts
Nice tool to help simplify data.
I would have liked to see 30 secs spent on comparing the areas of Q1 to Median Vs Median to Q3. The area that is bigger show skewness towards that. If Q1 to Median is large than the data is skewed towards left and if Median to Q3 is large then the data is skewed to the right. It would be great if the box actually had the histogram of data superimposed to show the box quickly captures the skewness of the data set.
7:37 where did you get the 1st quartile which is 56,900 and the 3rd quartile which is 93,825. Please reply asap
It'd be nice if you could edit video tittles and add playlist and video numbers
can u please explain the in box plot comparison at 13.00 .
I mean why si the median of San Francisco not in the middle of the box?
I like the general idea of the boxplot visualization in the first half of the video, but I think it might be a little confusing to some students have the lines of the 1.5*IQR whiskers not actually be 1.5 times the width of the box in the graphic. It makes those limits look far too close to Q1 and Q3. It also might be useful to use the word "fence" since that's common in the intro literature.
this is new to me, but I can see how it would be helpfull
Hi Brandon, can you please tell me how 1.5*IQR is considered for lower and upper limit?
At around 9:30. How does the Q3 which is 93,825+(1.5*IQR)=93,825?
Thanks
how do ou determine the median' how is it different from the midpoint
Hi brandon, Appreciate your work, would be lovely to connect with you over Linkedin!!
Why dont u teach most used machine learning concepts in an easy way
When u have to self study this because your teacher was uncapable of teaching via Zoom and now u need the knowledge desperately
Thanks