Binomial Distribution in R | R Tutorial 3.1| MarinStatsLectures

In this R tutorial, you will learn to calculate probabilities for binomial random variables in R. Here we will use the "pbinom" and "dbinom" functions in R to calculate probabilities for the binomial random variables. We will also use "dbinom" function to have multiple probabilities returned in R and "sum" function in R to calculate cumulative probabilities for the binomial random variable. You will also learn to calculate cumulative probabilities in R for the binomial random variable using the "pbinom" function.

Table of Content:

0:00:10 introducing the binomial random variable used in this video and its characteristics
0:00:24 how to calculate probabilities for the binomial random variable in R using the "pbinom" or "dbinom" functions
0:00:32 how to access the help menu in R for calculating probabilities for binomial random variables
0:00:43 how to use the "dbinom" function in R to calculate probability for the binomial random variable
0:01:24 how to have multiple probabilities returned in R for the binomial random variable using the "dbinom" command
0:02:10 how to calculate cumulative probabilities in R for the binomial random variable using the "sum" function
0:02:45 how to calculate cumulative probabilities in R for the binomial random variable using the "pbinom" function
0:03:30 How to use "rbinom" function in R (to take random samples from a binomial distribution)
0:03:38 How to use "qbinom" function in R (to find quantiles for a binomial distribution)

These video tutorials are useful for anyone interested in learning data science and statistics with R programming language using RStudio.

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Our Team:
Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC.
Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH)

These videos are created by #marinstatslectures to support some courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free.

Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!

[michaeld]

Many, many years later and this video is still helpful. Thank you !

[alexandremondaini]

you're the guy, thanks for your videos, concise to the point !

[scanguru]

Really good videos, simple and concise. Thanks for posting these for us to learn.

[elvinmirzayev]

thanks a lot for the a clear explanation.

[giannisbk]

bro you are a life saver. thank you so

[杨光垚]

3q so much, that's very helpful to learn R$statistics.

[marinstatlectures]

You're welcome, happy they can be of help ;-)

[SONU]

thanx a lot man...it helped me too much...

[ΓιωργοςΓαλάρης-ψβ]

Very helpfull videos!!!! Share on Facebook!!!!

[mansimehrotra]

Hello,
Can you please explain the implication of dbinom, pbinom and on what basis do we determine the number of trials and the probability which in this case is 1/6?
Thanks!

[azkatouhidadaiby]

for x>=something, the lower tail becomes false and do we have to use x-1?please reply.

[meenakshigautam]

sir if i generate binomial sample rbinom(1, 10, 0.2) but i only want my values between 2 to 9 ....how can I di that?

[thejokercrypto]

What happens if you want x > 2? how would I write it

[vridhikamboj]

what would happen if in pbinom statement we use lower tail=F.

[ssjvrn]

.our normal distribution does not discuss rbinom and qbinom. Please let me know which video it is or can you make one on those commands?

[gannsebastianquiban]

where did you get the 1/6?
please explain thank you!

[briandicapetti]

Help!!! Why can't I get the x=0, ..., 4 to work in dbinom(x=0, ..., 4, size=12, prob=.2) when I am trying to solve for the prob on 4 or less???? This is what they give on the r studio website to solve for a summed prob on getting" x or less" right(success).

[potubharath]

Sir, i am bharath
i want manual explanation of binomial distribution. Because in examination not provide R tool. The exam written only white paper. please explain the same R example in standard binomial distribution formula.

[alimjunaid]

Can we put Error value in place of P-value to calculate Probability

[appropiate]

isnt it lower.tail=TRUE by default and therefore no need to specify it when P<= is wanted?