Plots for Two Variables | Statistics Tutorial | MarinStatsLectures

Plots for Two Variables with Examples; Learn about different options for plots that can be made to examine the relationship between 2 variables. 👍🏼Best Statistics & R Programming Language Tutorials: ( goo.gl/4vDQzT )
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This video presents some different options for plots that can be made to examine the relationship between 2 variables. Plots exploring the relationship between variables is extremely valuable. It can help us visualize and understand the nature of a relationship between variables in a way that simple numeric summaries cannot. It can also help inform any analysis we may choose to conduct. As noted previously, the types of plots we make depend on the types of variables we have. Here, the plots are separated based on whether the variables are Categorical and/or Numeric. In this video, we learn when to use side by side boxplots, stacked bar charts, clustered bar charts, mosaic plots, scatter plots to explore the relationship between our variables.
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[@marinstatlectures]

In this #statistics video we learn when to use side by side boxplots, stacked bar charts, clustered bar charts, mosaic plots, and scatter plots to explore the relationship between our variables. Plots exploring the relationship between variables are extremely valuable. It can help us visualize and understand the nature of a relationship between variables in a way that simple numeric summaries cannot. 👍🏼Find the Best Statistics & #RStats Tutorials here: ( goo.gl/4vDQzT ) 🎗 Like to support us? You can Donate (bit.ly/2CWxnP2), Share our Videos, Leave us a Comment, Give us a Like or Write us a Review! Either way, We Thank You!

[@jeffreylin235]

I watch these videos to see how you teach these concepts. It helps me to explain things to my colleagues and peers. You are the best statistics instructors I've ever seen.

[@marinstatlectures]

thanks ;)

[@ernestoguevara8503]

binge watching queen's gambit? nah son, I binge watch MarinStatsLectures

[@marinstatlectures]

Lol, love it!

[@sureshgeddada6166]

Before watching your videos I've faced difficulty in understanding some concepts. But after watching your videos ,those concepts became very easy. Thank you sir

[@nedimkurt9009]

You're just amazing...and perfect! Thank you so much.

[@CORPSE77]

Thank you so much for your teaching. I want to cry because I am so happy I am finally understanding biostats. Thank you thank you thank you. I was wondering if you can provide a printout or a pdf please for these wonderful lectures?

[@raitup00]

Great ideas Mike

[@-lll7585]

Best stats tutorials!

[@yazminmojica4458]

Excellent! Thank you 🥀

[@marinstatlectures]

you're welcome :)

[@oiDATA]

Man.. It is a very interesting video, it is EXCELLENT. ¿Can you please, write te analyisis proofs used for every kind of analysis, acording to the kind of variables? I am not so fluently listening english and I can't get understand all methods that you mentioned.... Thanks a lot.

stonemonroy 1 cat + 1 num: Anova; two-sample t-test. 2 cat: Chi-square; Fishers test; OR: RR. 2 num: Pearsons’ correlation; Spearman’s; and Simple linear regression

[@oiDATA]

@ thanks a lot.

[@marinstatlectures]

bonus marks ;)

MarinStatsLectures- R Programming & Statistics (✌ﾟ∀ﾟ)

[@sb-hf7tw]

Plzzzz make some video on 01~one way anova, 02~two way anova without replication and 03~two way anova with replication i.e. equal number of observations per cell in R with proper real life examples..........🙏🙏🙏

[@marinstatlectures]

we likely won't make any videos on two-way ANOVA as it's not particularly useful in my opinion. you can get the same, and more, by just fitting a regression model that includes the two factors as x-variables. that is the way i teach it in my classes, and we really only present ANOVA as sort of a stepping-stone up to regression models.

[@Shivam_0786]

i hope u like the videos (baby not said)

[@fauziyakhan1214]

WOnderful way of explaining one of the boring subject..

[@digitaljeepney4440]

i appreciate you, but why are you so fond of cancer? it's a little depressing.