Statistics 101: Descriptive Statistics, Percentiles and Quartiles
HTML-код
- Опубликовано: 15 июл 2024
- Percentiles and quartiles are fundamental building blocks for statistics and data analysis. In this video, we learn about percentiles, quartiles, quintiles, and deciles. We learn how to visualize, compute, and interpret each measure. 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
Happy learning!
#statistics #regression #machinelearning
You are the only reason I'm passing Mathematical Modelling 2 at UTS. Thank you so much, these videos are amazing!
Always very clear, concise and understandable. Thank you, Brandon!!!
Oh my god Brandon you funny man :) Thanks for a great 2-week course in statistics. This is truly the best source I have ever found.
This is the best ever explanation of percentile system. In the past I’ve always struggled with this concept. Thanks a million!
Great to see you are still making content, awesome as usual
You are great help man. Much love for ur work !
1:33 - AWESOME !!!
I am searching for a Percentile exact formula and how it works in the case of a non-sequential list. finally understood ...Thanks a lot.
Thnks from india
You are making me to love statistics.
Good Lecture..
Hi Brandon, good video as always. Would you mind to briefly discuss/explain how the percentile value calculation formula was derived? Thanks
Excellent
Just Love Boss
Amazing way to segue into boxplots :)
Why is there a 0.5 in the percentile formula? I get that it is a correction for equal values and in my mind it makes sense for two equal values, but will this remain 0.5 if there are for example 7 equal values? And if so why? Thanks for the great videos!
Hi Brandon, Thank you for the awesome statistics videos. You have really done a beautiful job. Permit me to screen shots all your presentations so I can it to create my lecture note
While calculating the values (not positions) of quartiles in the example (@11:18) so we take assumptions about the distribution of the data like it being normal?
Hi, Mr. Brandon. I have a question for you. How to point quartile at particular site i.e. in between observations I have if the value of observation is an odd number, let's say 13 observation instead of your example shown as an even number of 12 observations. Thank you.
I have a few thoughts coming in my head, but I would like to hear your idea. :)
Hi Brandon, is there a reason to use two separate formulas for the same thing? I mean the formula at 18:30 and the one at 7:40 both give different results and I think they shouldn't. Am I missing sth?
Didn't Q1 quartile (3.25) miss her spot on plotting chart? Make it clear, please.
Hi Brandon. You specifically say there are 4 quartiles (with 3 values in each). But there is only Q1 (lower quartile), Q2 (Median) and Q3 (higher quartile) in your video. Where is Q4?
Hi! Q1, Q2, and Q3 are the boundaries that split the observations into 1/4ths or 25% segments. Like cutting a strip of paper into 4 equal pieces only requires three cuts.
Yes, I understand that. I got confused because quartile seems to designate two things, the boundaries and the segments. You say in the example, the dataset is split into four quartiles, each with 3 observations. Or am I missing something?
I thought you mentioned quartiles as having 4 equal parts, how come 5:14 is showing just 3 quartiles?
Very clear now at 6:57
0.375 rounded up to 38th Percentile? It's 1:53 am and I've been studying since 7 pm. sigh..