R demo | Chi-Square Test | How to conduct, visualize and interpret | + pairwise post-hoc tests

[@hikeaway1596]

I can't stop watching your videos ;) please produce more of them, It's really fun to learn from your content.

[@yuzaR-Data-Science]

learning addiction is the best addiction ever! ;)

[@jammaningas8850]

Very easy to follow! Nice!

[@yuzaR-Data-Science]

Glad you think so! 🙏 you might like other videos too 😉

[@ManuelAlejandroCastroGarcia]

Thanks for sharing your knowledge. How can I add the Yate´s correction into the plot?

[@yuzaR-Data-Science]

Unfortunately, either not possible, or I don't know why and how. But thanks for good feedback!

[@osmanhabeeb9892]

I was looking for the means separation of chi-square test in R. THANKS ALOT.

[@yuzaR-Data-Science]

I am glad it was useful!

[@JohnLee-pi5qx]

Thanks for the great video! Any tips for changing colors of the bars?

[@yuzaR-Data-Science]

Thanks, mate, sure: library(ggplot2) ggbarstats(mtcars, am, cyl, results.subtitle = FALSE) + scale_fill_manual(values = c("#E7298A", "#66A61E"))

[@neleluisa9210]

this was very helpful, thank you! Is there a way to calculate Cramer's V for the pairwise post hoc tests?

[@yuzaR-Data-Science]

Not yet! But it's a great question. I have to google it first. There is another cool package, I did not do a review yet - effectsize. Check out whether this one does the job. Thanks you for watching!

[@dewidinevandercolff3999]

Thanks, this was really easy to follow!

[@yuzaR-Data-Science]

Great to hear! Thanks!

[@andreapaolacotesperdomo2293]

Hi, great tutorial, many thanks! Any advise for comparison of one continuos vs one categorical variable?

[@yuzaR-Data-Science]

thanks! sure, I have similar short video of t-test, Wilcoxon, ANOVA, Kruskal-Wallis, Repeated Measures ANOVA, Friedman .... they all deas with one continuous and one categorical variables, check them out and find what fits your need best. Cheers and thank you for watching!

[@andreapaolacotesperdomo2293]

@@yuzaR-Data-Science thank you very much 😁

[@yuzaR-Data-Science]

@@andreapaolacotesperdomo2293 you are welcome!

[@Ange-y1k]

First of all, thank you. The video may be old, but I'm only watching it now. How do you go about post-hoc testing when comparing two variables with more than two categories? (I am having an error saying: 'x' must have 2 columns)

[@yuzaR-Data-Science]

hi, your error message is most likely due to having only 1 category, not >2. sure, you can do post-hocs easily, here is how, but I think I talked about it in the video: install.packages("rstatix") library(rstatix) contingency_table

[@Ange-y1k]

@@yuzaR-Data-Science Thank you for your answer. I used the same code, but replaced it with variables, each with 3 categories, it didn't work and gave me that code error.

[@yuzaR-Data-Science]

again, >2 categories is not the problem. here is the proof for two categorical variables with 3 categories each: ggstatsplot::ggbarstats(mtcars, cyl, gear). Something is wrong in your data, may be in your table, or some packages are not installed.

[@ouss991]

Thanks Yuri, great tutorial as usual. I have a question : can I actually use these plots in a paper or thesis, or do I have to create a conventional barplot without the stats?

[@yuzaR-Data-Science]

Hey Ouss, you can absolutely use them for a paper. They make your text cleaner, because you have all the stats on the plot, and not in the brackets, which disterbs the flow. You can do both, 1) save the plot with ggsave, where you can adjust everything, like size etc. and 2) you can create you own plot and use package "statsexpressions" from the same creator as "ggstatsplot" to add statistics to your own custom plot. Cheers.

[@ouss991]

Great. Thanks for the quick response. Looking forward to new videos 🙏

[@yuzaR-Data-Science]

you are very welcome :) more videos are on the way ;) thanks for watching!!!

[@evansnyanney7431]

I tried using it but I am facing lil bit difficulties- that ! Can’t convert to a symbol

[@yuzaR-Data-Science]

convert it to a factor: data %>% factor(bla = factor(bla))

[@so4ragb]

thanks, great tut

[@yuzaR-Data-Science]

You are welcome!

[@ecovisionando]

Thanks 😀

[@yuzaR-Data-Science]

You're very welcome 😊

[@siriyakcr]

🥰🥰 super yuri

[@yuzaR-Data-Science]

Thanks, Siriyak!

[@ManuelAlejandroCastroGarcia]

Thanks for sharing your knowledge. How can I add the Yate´s correction into the plot?

[@yuzaR-Data-Science]

Unfortunately, either not possible, or I don't know why and how. But thanks for good feedback!