Variables and Types of Variables | Statistics Tutorial | MarinStatsLectures

Variables and Types of Variables in Statistics- Learn the difference between numeric (Quantitative) variables and categorical (Qualitative) variables working through multiple examples!
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When collecting data, we record and analyze "variables" This video describes the different types of variables we can collect. It also makes note of the various names you may hear for these, as different disciplines tend to use different names for the same concept/idea.
This is important as the way we summarize, plot, and analyze data (topics coming up) depends largely on the type of variable(s) we have.
►► Watch More:
► Statistics Course for Data Science bit.ly/2SQOxDH
►R Course for Beginners: bit.ly/1A1Pixc
►Getting Started with R using R Studio (Series 1): bit.ly/2PkTneg
►Graphs and Descriptive Statistics in R using R Studio (Series 2): bit.ly/2PkTneg
►Probability distributions in R using R Studio (Series 3): bit.ly/2AT3wpI
►Bivariate analysis in R using R Studio (Series 4): bit.ly/2SXvcRi
►Linear Regression in R using R Studio (Series 5): bit.ly/1iytAtm
►ANOVA Statistics and ANOVA with R using R Studio : bit.ly/2zBwjgL
►Hypothesis Testing Videos: bit.ly/2Ff3J9e
►Linear Regression Statistics and Linear Regression with R : bit.ly/2z8fXg1
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[@marinstatlectures]

In this video we will learn about the different types of variables in statistics and in research. We will go over numeric and categorical variables and their sub categories (continuous/ discreet) and (ordinal / nominal). In this tutorial, we will work through multiple examples to understand the differences between the variables better. If you like to support us, you can Donate (bit.ly/2CWxnP2), Share our Videos, Leave us a Comment and Give us a Like 👍🏼! Either way We Thank You!

[@shubhammishr]

Gender, Skin Color, Hair Color is an attribute as well as a variable?

[@chopsp5370]

What a gift to humanity this guy is

[@karlleroux9461]

Thank you, clear and very helpful! It is amazing that you make all your lectures available online - thank you and kudos to you!!

[@victoriaaikins6588]

Thank you so much!!! I sat in a lecture hall for 1 hour and did not understand this topic. Thanks to you I am almost a guru. I am all smiles. Thank you!!. I have subscribed to your videos.

[@lexwarden309]

Wow, You're a great teacher! Nice explanations, thank you for this!

[@aymanfakih8643]

Amazing pedagogy! Thank you so much for explaining variables in a structured manner. Now you have one more loyal subscriber for sure!

[@Zak_MZ]

This is amazing. I loved this since it is super easy to understand.

[@AIology2022]

Thank you for your valuable videos. Those are really significant!

[@jean-yvesberisse4512]

This is such an instructive class. THANK YOU SO MUCH.

[@lorenzodedios1303]

Thank you so much, God bless you for making it simple, with hierarchies which ones belong together or under. Glad people made videos of their lectures for future users.

[@keena2505]

Thank you for such great explanation! Very easy to follow

[@paulels3022]

Really appreciate the good explanations in this video. It helped me to understand it better. Thanks

[@hannahbolton6900]

So helpful. Recently decided to go back to college and I am taking statistics and have not done math in over 10 years. Learned more in this than my 45 minute lecture.

[@marinstatlectures]

Good luck with the journey :) we have videos covering likely everything you’ll need. I created most of these for my stats courses at UBC

[@AbhishekAlate]

Oh my god, the outro audio on the video was so adorable!

[@petere.anakwe2495]

Thank you very much for this video. Great explanation!

[@ikuzwefiacre8219]

This was very helpful, and thank you so much!!!

[@aliyaomanova9408]

Thank you a lot for such an informative and helpful video!

[@MarianaC192]

So helpful. Thank you!

[@emilytorres3992]

Thank you for making this video!

[@glam_style_ride]

Thank you so much. This video clarified a lot of things for me.

[@lakshmiaparnavaliveti6309]

Just love this explanation, this blew away all my doubts.

[@chandrapaulramsamooj2906]

Thank you for the explanation. very simple and direct.

[@LilithsErrand]

This made understanding different variables so simple! 'Categorizing' them this way made it easier to understand without having to memorize definitions -- thank you!

[@tuasonbeast8144]

Can I ask? If yes, what type of variable is values?

[@HyperDangerousThing]

@@tuasonbeast8144 like life values? if yes, its categorical and nominal

[@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

[@snaicker4433]

Great lecture, love it

[@mbz205]

Love the way you lay everything out. Its easy to understand. My stats textbook is full with big words. Let me understand the concept first. Love it man. I will definitely recommend my classmates to this video.

[@marinstatlectures]

Good to hear! We have videos covering most material presented in into stats courses (as I created them for my intro stats course), so you can check out them for any other topics in your course

[@JeffreyMonge-uz1mp]

Thank you for helping me. Taking statistics starting this week.

[@FatemeSafaei99]

I got it finally once forever. THANKS

[@mamtasinghchauhan9353]

Great video and I agree with the Child you are definitely a statistical ninja😊

[@user-zr6qg9td4u]

very clear and soo helpful. Thank you

[@sabrayahya89]

thank you Sir,..this was so helpful

[@deepika2830]

Omg...this is sooo helpful. Thanku😊😊😊😊😊

[@raitup00]

Great videos Mike 😀

[@afonsoosorio2099]

Awesome 👌, Dad is absolutely statistics ninja and he nails it.

[@pm490]

thank you sir this was really helpful :)

[@monicak6159]

Thank you for this!

[@zerocarb4892]

such a good Teacher well done !

[@gnalyseydi9918]

Thanks so much!

[@nandibwanali5624]

Super helpful!!!

[@ProminanceChinembiri-ez7cj]

its so powerful and simple to understand it l like the way you explain it

[@ernestoguevara8503]

I've been learning a lot from your videos, thanks a lot!

[@marinstatlectures]

Great to hear! You’re welcome :)

[@susanatinoco8861]

This was more helpful than my professor. Thank you 🙏

[@bountifuloptions]

Your girl's voice is so inspiring for me, always making me come back to watch this video

[@hbdxxm]

great tutorial！you know statistics better than my teacher!

[@Alhosanih88]

you saved my day mate 😁😁

[@aaronsarinana1654]

Great lecture. Thanks!

[@marinstatlectures]

You’re welcome, happy to hear you’re enjoying them :)

[@thandiwezawe8650]

Thank you so much sir

[@dulaababa3824]

❤❤❤ thank you

[@praveenbhatt3127]

great video.

[@statisticslearning]

Very nice

[@gf-cq1wf]

Easy to understand

[@chesteremmanuel3943]

thankssss :DD

[@Happyticcer]

That actually wasn't painful..... thank you

[@ThowathDakBeliewYar-ds8kg]

I like this ❤😂

[@jalal5773]

Thanks

[@Fishysalmon02]

would temperature in Kelvin be a discrete variable? since its 0 is actually the absence of heat/energy, therefore making it a meaningful ratio

[@fikrumara892]

good presentation

[@marinstatlectures]

thanks :)

[@debrafrederick5300]

Is there a text that I could purchase that would go along with this course? I do appreciate this. So far, I am not lost. My plan is to finish your series before taking an Introductory Statistics in college. I do not feel ready to jump into a graded course just yet.

[@neenaji1]

The question is about variables. We would say that “height” is a variable. In my mind, “height” does not just represent different values, like 2, 45, or 75. It represents values + units: 2 feet, 45 feet, or 75 feet. However, when we work with variables mathematically, I believe that we think of them as solely representing values / numbers. For example, we will say statements such as: height = 2 weight = height + 4 weight = 6 It seems confusing to me to have to think about variables in 2 different ways. Could you explain if I’m thinking correctly? How do you recommend thinking about variables so that I can do statistics most effectively? Please reply. Thank you

[@joina9545]

Hi, so variable age is cont how i understand. Can we use Gauss distribution for her? :)

[@Ahmed-jl7uh]

Is there any E-Book or PDF file for this series of statistics?

[@hareezvizard9233]

if the range of age is limited as for example age between 15-18, is that consider categorical or continuous? I'm confused

[@abhishek-shrm]

Statistics Ninja What a cool name for statisticians😂😂 I wanna be one as well.

[@user-kc2cq4rv4i]

were you really writing it mirrored? cuz that's cool and besides the topic i would love to learn that from you as well ,,,,,btw thankyou for this video!:)

[@rkhello]

Incident - Time, Incident- Latitude and Incident- Longitude - If I have data captured for an incident with Time, and Location ( Longitude, latitude) , what type of variable will they be called ?

[@hanshineem5424]

Thank you for this! Although I have a question. In which variable would you classify the following? Age group: 0-20/21-40/41-60/61-80/81+ Does it fall into nominal as a defined category or ordinal or another variable?

[@marinstatlectures]

It’s a categorical variable, on an ordinal scale

[@arlabs2506]

Marin, Could you please let me know on what way you made this video...did you record the mirror before which you are standing writing on the glass board or how actually ???

[@Zosime22]

Agreed. I was just wondering is he was writing backwards on a glass in front of him.

[@PC-rv9bp]

They draw it on their side of the glass and reverse the video in editing

[@koparka112]

Actually temperature in Kelvins has a meaningful (physically) zero... Thank you for all the videos. Happy New Year

[@MohitChaudhary2597]

but it is still interval variable e.g. uk shoe size 12 if we divide it by 2 it will uk size 6 but does it the exact half size of uk 12

[@abdulmueed5819]

What about absolute zero on the Kelvin scale? That has a meaningful zero. So would temperature measures be classified as having a ratio scale?

[@kowsarhoney9754]

Temperature is interval if I’m not wrong.

[@skeeterburke]

🤔 does it simplify statistical calculations involving temperature if you use Kelvin?

[@marinstatlectures]

Not really, it’s just using different units for the variable.

[@ABSP5766]

Great course! I was wondering if hair color could be considered ordinal instead, since it depends on the amount of melanin (I think) and it can be ordered from lighter to darker (or vice versa )

[@gendertreachery]

If the amount of melanin is the focus of the study, yes. Then the variable would be "the amount of melanin." But in most cases that is not the case.

[@afonsoosorio2099]

Kirk is is absolutely right ✅, but it can be arguably ordered since there is a gradient scale, specially when it comes to visualization. This brings us to what is known as factor data type in R programming

[@KnowledgeHub79]

sir when age is converted in categories like 1.1-10,2.10-20,...... is ordinal then?

[@marinstatlectures]

yes that's correct.

[@KnowledgeHub79]

@@marinstatlectures thank you sir!

[@TechCubes-or1tw]

Martin I believe income is a discrete variable and not a continuous. Consider it this way the age is continuous as we cannot skip any interval. like a man can't be 30 this year and will be 35 next year, he will touch 31 then 32 and so on. But salary of person can skip few intervals like I can have 30k salary this year and can have 90k salary next year. I do not have to first get 31k then 32k and so on. I can skip intervals.

[@marinstatlectures]

Continuous means it is measured on a continuous scale, not a discrete one. But there isn’t a big difference in how we treat continuous vs discrete variables, especially for a discrete variable that can take on many possible values

[@dee.0]

you teach better than my stupid professor

[@danialmalik80]

Marin What is BMI numerical or continous, my guess is it is continous due to it can be measured

[@marinstatlectures]

Hi Daniel, Numeric variables can be subdivided into 2 groups, Continuous and Discrete. BMI is a numerical variable measured on a continuous scale (discrete variables only take on integer values, continuous variables can take on non integer values). In practice, there isn’t much difference in how continuous/discrete variables are treated in analysis

[@danialmalik80]

@@marinstatlectures Thank u so much

[@yogalshmitp3660]

does soccer positions(defender, midfielder ,forward) have ordinal scale of measurement . i don't know about soccer as I am not interested in sports, but i need to answer this question for my statics assignment .Please help me in this

[@afonsoosorio2099]

What are measuring on soccer ⚽️ positions? Is position a variable that can varies, takes many values and can be measured?

[@arpitbapna9512]

Are discrete variables always only integers? Can't a number like 4.5 or 5.5 be a discrete variable? For example: Can't we use the Shoe sizes variable as discrete variables four, 4.5, five, 5.5, and six? Does it makes sense? or I'm just getting confused?

[@afonsoosorio2099]

Good one. I guess shoe 👞 size just like age, height, weight are continuous variable as they can be measured and take decimal values. A good remark the lecture made on numerical variables is that they can be broken into categories and grouped then ordered. Look at age (child, infant, teenage,....), weight (underweight, over, obese), height (short, tall,....). Now looking at it from measurement scale, when you convert a continuous variable measured in ratio scale, into a cat ordinal variable, it does not hold any longer the ratio scale. This is how I would look into the question you raised. Hoping not getting you confused

[@KnowledgeHub79]

time of day (morning,noon ,after noon,evening,night) is it nominal or ordinal?

[@marinstatlectures]

it partly depends on how you are using the variable. if you are using it with the ranks/ordering meaningful, then id consider it ordinal

[@KnowledgeHub79]

@@marinstatlectures sir isn't it give sense of order it self like dawn is to come first then mornin and so on?

[@binupandey6247]

​​​@@KnowledgeHub79 The time of day (morning, afternoon, evening) can be considered ordinal. Ordinal data represents categories with a clear order or ranking, but the intervals between the categories are not necessarily equal. In this case, morning comes before afternoon, and afternoon comes before evening, so there is a clear order to these categories. However, the time intervals between them are not uniform or equal.

[@khiannecruz7967]

Whats the comparison between independent variables, dependent variables and control variabless Someone answer now pls

[@marinstatlectures]

Often one is interested in examining the effect of an independent variable (X1) on a dependent variable (Y), while controlling for other variables such as confounders, etc (X2, X3,...are the control variables)

[@Bob-go2gn]

Umm, i just wanted to ask the difference of continous and discrete variables.

[@KnowledgeHub79]

age (in years) is ratio?

[@marinstatlectures]

yes it's ratio, as here an age of 40 is double the age of 20 (while something like temperature is NOT ratio as a ratio is not meaningful in that a temperature of 20 is not twice as hot as 10). hope that made sense...

[@KnowledgeHub79]

@@marinstatlectures ok thanks sir

[@rikicade2012]

on 5.05 you said age is continues isn't discrete?? age is integer 33 34 60 80 29 etc as you said age cant be 35 and 888 either is 35 or 36 i could be not catch that part please correct me thanks

[@marinstatlectures]

Well, technically age is continuous, but we usually report age to the nearest integer (truncating the decimal place). But we treat continuous and discrete variables pretty much the same when analyzing, when a discrete variable takes on a large number of values. So it doesn’t matter too much in this case. Hope that helps clarify it

[@rikicade2012]

Thanks

[@giftzulu8156]

Is age really continuous? Going by the definition of discrete variables, I would think that age is discrete. Please kindly clarify. Thank you.

[@marinstatlectures]

Age is continuous, we just report age in whole years. But one one turns 20, then after 36 days have passed they are 20.1, and 18 days after their 20th birthday they are 20.05, and so on. But no one says they are 20.548 years old, they just say 20. But it is actually measured on a continuous scale. A discrete variable is something like the number of people in a room. It is 0, or 1, or 2,… there can not be 2.53 people in a room. It only takes in integer values. It is worth mentioning that there is only a very small difference with how we treat continuous and discrete variables

[@afonsoosorio2099]

Age is associated with time. Years, months, weeks, day, hours, mints, seconds,... and there should be no dought that it is a continuous variable!

[@samuelwong6352]

5:07

[@shruti9550]

Category to numerical conversion not possible?

[@marinstatlectures]

No it’s not. Consider biological sex...there is no way to convert male/female into numbers. You can use something like 0/1 to code it, but it would still be a nominal categorical variable

[@shruti9550]

MarinStatsLectures- R Programming & Statistics But when want to perform PCA , it’s compulsory veritable are numerical dataset We use dummy variables to convert categorical variables to numerical variables so what exactly happened behind screen ?

[@marinstatlectures]

Well, a dummy variable isn’t numeric. What those do is use an “indicator” that equals 1 when you’re in a group, and 0 when you’re not. Those are just a way to include categorical variables into an analysis...but it is not converting them to numeric

[@translucent0724]

Types of data and types of variable same?

[@afonsoosorio2099]

Good one. Just making a summary on that one. They are intertwined. In dummy language variables are related to how data or observations are recorded. Data types is how data is stored in computer 🖥 memory, handled and manipulated. Each programming language has its own data types are can overlap. Common data types are numeric (integer, decimal), characters (strings), date 📅, ..... logical (boolean), .....

[@alexneigh7089]

... or 0 degrees Kelvin.

[@absnotafairy]

omgg ur daughter is so cuteee

[@seanbrendangarrette7644]

Am confused here, isn’t 30 degrees twice as hot as 15 degrees?

[@ananyagupta4824]

same that threw me off! Is that something I didn't know or am I tripping because the numerical value of a degree is fixed so..??

[@phillipgiwu9683]

The screen is so clumsy with your creative presentation. It's difficult to follow it

[@jaquezm00]

is this guy writing backwards????

[@arlabs2506]

Maybe he is using a Smart board..I guess.. Only Mike can let us know... Could you plz tell us Mike...what way you make this video ?

[@user-katr]

no, the video is flipped

[@glam_style_ride]

🤓

[@Sagebeige_together]

You’re writing backwards?!

[@Arthur-hg7ny]

I believe Likert is pronounced “Lick-ert’

[@nilavazhagana4691]

Ahhh I hate statistics Thanks for explaining

[@elextinto]

Sus

[@neenaji1]

The question is about variables. We would say that “height” is a variable. In my mind, “height” does not just represent different values, like 2, 45, or 75. It represents values + units: 2 feet, 45 feet, or 75 feet. However, when we work with variables mathematically, I believe that we think of them as solely representing values / numbers. For example, we will say statements such as: height = 2 weight = height + 4 weight = 6 It seems confusing to me to have to think about variables in 2 different ways. Could you explain if I’m thinking correctly? How do you recommend thinking about variables so that I can do statistics most effectively? Please reply. Thank you