R demo | Two-Samples t-Test | Student’s & Welch’s | How to conduct, visualise, interpret & more 😉
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- Опубликовано: 21 авг 2024
- Where can we get more money, working in a factory or in the IT-industry? Two-samples t-test will answer this question. So, let’s learn (1) how to make sure we use a CORRECT test, (2) how to get all these results with one simple command, (3) how to interpret all these results and (4) finally see what happens if we choose a wrong test.
If you only want the code (or want to support me), consider join the channel (join button below any of the videos), because I provide the code upon members requests.
Enjoy! 🥳
The first time I went through the video I was just interested in the R part of it. Today I've learned more from the information shared here in. Thank you for the great video.
Glad it was helpful! :) Feel free to share it with others who might find it useful and thanks for watching!
@@yuzaR-Data-Science Noted
Absolutely loved the presentation !
Glad you enjoyed it! Hope you like the rest too.
Very helpful video! It introduced the most practical and convenient function tools! Your voice is also very magnetic.
Glad it was helpful! Hope the others are helpful too. Thanks for feedback and for watching!
This video actually is a hidden gem. Thank you, Sir. I've learnt a lot today.
So nice of you! Glad it was useful! Hope you like some other of my videos too. Thanks for watching!
I'm loving your videos, all is clearly explained.
Happy to hear that! Thanks for watching!
Excellent video🙌 It would be great a video of bayesian analysis
Noted! Thanks for your positive feedback! 🙏
A very nice lecture Sir 👍👍.
Thanks and welcome!
Sir please make videos on Bayesian.
I will eventually, but it could take some time. So, please, use other study-resources in the meanwhile and then you'll be able to compare with this channel, when I come up with those. Cheers
Love this! thanks for sharing it.
Is it possible to report the Bayesian output based on B10, as opposed to B01?
Not that I know of. The package doesn't provide any arguments for it, but you could the author of the package on his github page or on twitter. Cheers
@@yuzaR-Data-Sciencemany thanks 👍
@@jonrrobinson welcome! 🙂
valuable assistance for violin plots...please provide reference for bias factor table at 5:03
The original is from the book: "Jeffreys, Harold. The theory of probability. OuP Oxford, 1998.", but you can also see it used in papers like this one:
journals.sagepub.com/doi/10.1177/0049124117729712
Excelent explanation, but, how can I increase the fontsize of the equations in the plot to save it as a figure?
Thanks! I usually use ggsave() and make the plot smaller with width and height arguments. That makes the font larger automatically. Until now nobody complaned about small font ;)
@@yuzaR-Data-Science thank you so much, sir! I was saving 4 plots of these, tried using first the ggarrange to combine the ggplot objects than using the jpeg function, and I don't know what happened but even using smaller height and width values the fontsize of the equations kept low, now I'll try with ggsave. Thank you so much 😉
oh yeah, there is one bug in saving you have to watch out: "device" argument:
ggsave("name.jpg", plot = last_plot(),
width = 19, height = 11,
device=jpeg)
ggarrange actually works fine too! if not, try out "patchwork" package
Why in this case the pairwise comparison horizontal bar didn’t appear?
Because those are independent samples. For horizontal bars to appear you need a paired t test, which is a completely different video because it is a completely different test. So, make sure you use a correct test on your data.