Box-Plot (Simply explained and create online)

In this tutorial you will learn what a boxplot is, what information can be read in a boxplot and then we will look at what we have learned with an example.
Boxplots are used in statistics to graphically display different parameters at a glance. This is why boxplots are so difficult to understand at the beginning, because a lot of information about the data is provided in one diagram. Among other things, the median, the interquartile range and the outliers can be read in a boxplot.
The data used must have metric scale level. Such as a person's age, annual household electricity consumption, or temperature.
What is the interpretation in a boxplot?
The box itself indicates the range in which the middle 50% of all values lie. Thus, the lower end of the box is the 1st quartile and the upper end is the 3rd quartile. Therefore below q1 lie 25% of the data and above q3 lie 25% of the data, in the box itself lie 50% of your data.
In the boxplot, the solid line indicates the median and the dashed line indicates the mean.
For example, if the median is 34, that means that half of the participants are younger than 34 and the other half are older than 34. The median thus divides the people into two equal groups.
The T-shaped whiskers in the boxplot go to the last point, which is still within 1.5 times the interquartile range. What does it mean? The T-shaped whisker is either the maximum value of your data but at most 1.5 times the interquartile range. Therefore, if you have an outlier, then the whisker goes up to 1.5 times the interquartile range. If there is no outlier, the whisker is the maximum value.
So the upper whisker is either the maximum value or 1.5 times the interquartile range. Depending on which value is smaller. Exactly the same applies to the lower whisker in the boxplot, which is either the minimum or 1.5 times the interquartile range.
Points that are further away are considered outliers. If no point is further away than 1.5 times the interquartile range, the T-shaped whisker thus gives the maximum or minimum value.
More information on the boxplot:
datatab.net/tu...
Create boxplot online:
datatab.net/st...

[@datatab]

If you like, please find our e-Book here: datatab.net/statistics-book 😎

[@ruthgyereh1052]

How can I purchase this, please? Thanks.

[@memelchang]

As a medical student who has to take statistics in order to graduate, thank you so much. This video is a life saver. I really cannot express in words how grateful I am. A year of classes and I barely grasped the concepts of variables, but two minutes made it all finally make sense

[@datatab]

Many thanks!

[@shikha7873]

​​@@datatab mam when minimum value first quartile and median are same then we how to plot box please ma'am reply because tomorrow's the last date of submitting assignment of my college and this type of question I failed
to solve

[@TheNachoDaddy]

I came here to say the same thing. It’s amazing how much easier this is to understand when watching this presentation, versus reading it in a textbook.

[@jiggyfeets6050]

You are a life saver. I am a computer science student and i've never done anything with data or statistics but I got a competition tomorrow. You're a life saver

[@datatab]

Greate : )

[@phoenixblack1220]

Oh my God! Why can’t professors put as easily as you just did? Thank you so much! And thank you for the link to the data calculator!!

[@datatab]

Thanks : )

[@basquiatttt]

Today is a happy day for me as I finally grasped this, which I thought to be a very hard-to-understand chart. Thanks for the great explanation and tooling!

[@datatab]

Many thanks : )

[@svetlanama6814]

Thank you. I was confused why the whiskers were not the same length, but now I understand that one can indicate 1.5xIQR, while the other might show min/max value if there are no outliers.

[@datatab]

Happy to help!

[@ravitejadevarakonda9009]

Explained in a very simple and understandable manner 👍🏻

[@srsh12345]

Thank you for the breakdown. You helped me understand this topic much better.

[@datatab]

Glad it was helpful!

[@adityaagrawal2397]

That's how educational videos should be, to the point and concise, no useless blabbering !

[@datatab]

Thanks : )

[@shrikant301991]

Absolutely right !!!

[@simga849]

I have applied statistics course in my Master of data science. I have to say that watching 2 videos of you in 16 min made me understand perfectly 3h of lecture at University. Thanks for the Video. Keep it up😊

[@terran008]

Thank you, this was really comprehensible

[@datatab]

Glad it was helpful! Regards Hannah

[@mostafamarwanmostafa9975]

Thank You !! Very short , Informative and Excellent explanation!

[@ShohanDominic]

Easy to understand and well explained. Thanks

[@datatab]

Glad it was helpful!

[@NasrinSultana-i4r]

very good presentation . It would have been better if u had explained the last example Fall ( in four places) according to Age

[@MsLaBajo]

So helpful for my stats class! Thank you!

[@Geology_monster]

My God! your accent is so beautiful, thanks for the explanation.

[@muhammadhamzamaqsood8576]

thanks for explaining it in the easiest way

[@datatab]

Happy to help

[@LaunchBizNow]

Thank you so much for this great video. I understand a lot better.

[@datatab]

Glad it was helpful! Regards Hannah

[@izb1275]

Your website is amazing !!

[@datatab]

Thank you!

[@galeop]

Useful quote from wikedpia about whiskers:
_whiskers []are based on the 1.5 IQR (InterQuartile Range; ie the length of the box) value. From above the upper quartile (Q3), a distance of 1.5 times the IQR is measured out and a whisker is drawn up to the largest observed data point from the dataset that falls within this distance. Similarly, a distance of 1.5 times the IQR is measured out below the lower quartile (Q1) and a whisker is drawn down to the lowest observed data point from the dataset that falls within this distance. Because the whiskers must end at an observed data point, the whisker lengths can look unequal, even though 1.5 IQR is the same for both sides._

[@khalidsultani1896]

Thanks for posting this awesome explanation ❤

[@TochukwuVictor-qe4xd]

Super helpful. I love your presentation.

[@mannumichel1925]

Very Well Explained. Thank you.

[@datatab]

Thanks!

[@sandeepangadi9824]

Very much informative video

[@Neo-ef9zi]

Nice explanation ma'am....thank you!

[@superhessu3]

if there's no mean line in the boxplot does it mean the mean line would be on top of median

[@grace2714]

thank u so much! this was so easy to understand

[@datatab]

Glad it helped!

[@oalararua9853]

Good explanation!

[@vrindasharma4554]

Very well explained...thanks a lot...

[@MinhNhat-dk6xv]

Thank You so much!

[@vitaliyshastun4162]

Thanks! Easy to understand and clear ☀

[@tg-us3hw]

bruh, this is teaching me better than my lecturers

[@datatab]

Many thanks for your feedback! Regards, Hannah

[@vinodgujja4268]

Simply say, amazingly explained

[@datatab]

Glad you liked it

[@charafdev5702]

Great video, good explanation! Thanks :)

[@datatab]

Glad it was helpful!

[@kshitijchauhan1479]

thanks this was very helpful

[@ptseti]

excellent presentation. Thank you

[@mukeshprajapati2825]

good explanation

[@tybahfiras7983]

Thank you so much

[@akshitaarora5291]

Thank you 😊 it helped alot ❤️

[@datatab]

Glad it helped! Regards, Hannah

[@poojapathariya6070]

Nicely explained!!!

[@datatab]

Glad it was helpful!

[@amanpreetchander7386]

Very well explained.

[@anita18274]

i cannot find the sample data in the link you provided, it gives me another data set

[@KingfisherLtd]

Hi. It was a great lesson. What is the minimal number of variables to use a box plot graph? Is it 'the more data the better' rule like in histograms? Best wishes.

[@sumitmitra7336]

Very nicely explained. What does the length of the whisker signify? If the lower whisker is lesser in length, than the upper whisker , then what does that mean ?

[@stedomusic]

Means the lower quartile distribution is lower than the upper one

[@appusuriya6895]

Superb. Thank you so much for this video

[@datatab]

Thanks for the comment! Regards Mathias

[@albamoreno7016]

So useful :)

[@datatab]

Thanks : )

[@flow4009]

Great! Thanks :)

[@datatab]

You're welcome!

[@joyprokash4013]

Great mam.

[@datatab]

Thanks!

[@mousaedhoussen4129]

Thanks alot

[@datatab]

Most welcome

[@anurajms]

ty

[@datatab]

: )

[@judgementday7350]

Thank youuu

[@datatab]

You're welcome!

[@Montoloid]

Thx

[@BinweiYu]

interquatile range

[@rafidahmed1885]

1.5x

[@banyongadesmond]

nailed

[@benice6627]

Where's the q2 in this video?

[@diegofarmer708]

Median

[@JadenLockery]

A good video with an easy explanation for interpreting box plots however, silly example using the cliché men and women pay gap.. I know it was just an example but the pay gap does not exist. The pay gap is based off an overall statistic for the average pay of men and women. It is a multivariate equation as to why women earn less then men (on average). The first reason is the majority of men work in STEM related fields which earn more money whilst women tend to focus more on fields that work with people e.g. nurses, vets etc. Women can absolutely enter into STEM related fields but because of personality differences, not as many women do. Maternity leave is another factor that contributes to women being paid less. If you think about it, lets say for argument sake that the majority of women at some point will have a child at some point in their lives, that is 9 months without pay for every single woman who bares a child. There are many other variables as to why this so called "pay gap" exists but lets be clear it is not because men have some kind of unfair advantage, that is just victim mentality plain and simple.

[@transnaftaplatform2874]

I need the codes

[@mannygamingcodm]

The salary of Men and women representation isn’t necessary. Could have used another representation. But good work

[@datatab]

Thanks for your feedback!

[@MuhammadAhmed-jl6si]

STOP CRYING

[@kene5370]

The video did not helo me that much but tnx anyway

[@druell4u]

Well explained. Simple and intuitive

[@datatab]

Thanks : )

[@prasannabharathi2019]

Thank you so much

[@datatab]

You're most welcome

[@FaridLatiff]

Thank you so much!!!

[@datatab]

Glad it was helpful! Regards, Hannah

[@ReemManash]

You are amazing
This was the most valuable explanation that I have ever saw