Learning Objectives: Know what we buy estimates with Perfect fitting models Spent vs. unspent df Complexity vs. fit tradeoff Joe Rodgers's DF paper: journals.sagep...
I have to agree with Mendy, I don't understand why stats professors explain things by using more stats terms that they know their students are struggling to understand. Thank you for using human language! 😄
Lol this was awesome, despite super intense delivery it was really awesome with the old school 40s music, and made it feel wholesome. And very helpful metaphor.
Dude, I love you. You are amazing in so many ways. Your enthusiasm and levity combined with simple real world examples makes a boring AF subject come alive in more than one way! In particular, it makes more sense!!!
Hi, you talk about your Jasp module. Do you intent to implement it into jamovi as well (the Flexplot module in jamovi is less complete than its jasp counterpart)?
Great video as always! I know spending a lot of DF is bad, but I never really get the reason why. This video helps! EDIT: So then how's the remaining degrees of freedom used in a statistical test? Is it the actual "sample size" that we use to estimate our parameters?
The remaining degrees of freedom are used to compute P values. You may remember from intro stats that you had to look up the significant P value for a given test statistic (for example T), and for a given degrees of freedom.
I finally got clear the concept of degrees of freedom only after watching your videos. Great works keep it up!
Thanks!
I have to agree with Mendy, I don't understand why stats professors explain things by using more stats terms that they know their students are struggling to understand. Thank you for using human language! 😄
exactly!
Glad I could laugh. When I can get jokes about a concept, then I know I understand the concept, to some "degree". Thank you.
Lol this was awesome, despite super intense delivery it was really awesome with the old school 40s music, and made it feel wholesome. And very helpful metaphor.
My dude is a hypeman for statistics! Love it. Clear and engaging metafors, nice vid.
This has to be the best thing you've ever made for humanity. You made me smile. Thanks :)
Dude, I love you. You are amazing in so many ways. Your enthusiasm and levity combined with simple real world examples makes a boring AF subject come alive in more than one way! In particular, it makes more sense!!!
P.s also a photographer that is learning stats - albeit for psych ;)
P.p.s this is Fred the partner of Hannah >.
Thank you so much, you've helped a peruvian student
CZcams money pays for my meals.....I’ll watch more
The best explanation of SD.
Brilliant, best explanation I've heard
I love the way of Your teaching
These videos are excellent
I loved it! Very engaging 🔥
Awesome! Well done
OK, this was amazing.
These are very good videos. Thank you for making them.
OMG I was looking for someone who can teach stats like this! your videos are awesome and hilarious 😂 keep it up!
Thanks!
No problem!
Finally I understood it! Thank you. I hope you can gret some milk and eggs for that nice boy.
Your son is adorable! Give him all the ice cream he wants for breakfast!!!!
Terrific 🙏
mf explains this in 6minutes while my computational statistics professor cant explain this in 2 lectures
This was helpful. Thank you :)
what is a numerator df and a denominator df
Thank youuuuu
Hi, you talk about your Jasp module. Do you intent to implement it into jamovi as well (the Flexplot module in jamovi is less complete than its jasp counterpart)?
Kinda. I'm actually going to collaborate with the maker of the gamlj module for the automation of model graphics, then beef up the flexplot part.
Great video as always! I know spending a lot of DF is bad, but I never really get the reason why. This video helps!
EDIT: So then how's the remaining degrees of freedom used in a statistical test? Is it the actual "sample size" that we use to estimate our parameters?
The remaining degrees of freedom are used to compute P values. You may remember from intro stats that you had to look up the significant P value for a given test statistic (for example T), and for a given degrees of freedom.
Thanks! By the way, I really like your working hours metaphor. It is much easier to explain IMHO.
🙌🙌🙌💫
Hi! The link is not there for the paper you cited
It's there now :)
Detaaaa😂
I like your shirt
legend