Dummy Variables in Multiple Regression

In this video I explain what dummy variables are and how you can easily create them online.
Categorical variables with two characteristics can be used as independent variables (predictors) in a Regression. Variables with two characteristics are also called dichotomous, e.g. gender with the characteristics male and female
Normally, only independent variables with two characteristics can be considered in a regression. If the variables have more characteristics, dummy variables must be formed. From a variable with n characteristics, n-1 new dummy variables with 2 characteristics each are created.
You will find more information here:
datatab.net/tutorial/regression
and the online Regression Calculator:
datatab.net/statistics-calcul...
Regression Analysis: An introduction to Linear and Logistic Regression
• Regression Analysis: A...
Simple and Multiple Linear Regression
• Simple and Multiple Li...
Assumptions of Linear Regression
• Assumptions of Linear ...
Logistic Regression: An Introduction
• Logistic Regression: A...
Dummy Variables in Multiple Regression
• Dummy Variables in Mul...
Regression with categorical independent variables
• Regression with catego...
Multicollinearity
• Multicollinearity (in ...
Causality, Correlation and Regression
• Causality, Correlation...

[@datatab]

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

[@dukeislam6293]

Thank you. You provided the best explanation of "Dummy Variable".

[@Nick-px5tq]

Hah! I loved the n-1 reveal on car type dummy variables. As you were describing the initial 3 I was yelling at the screen "but these are mutually dependent - they break the assumptions!". I laughed at myself when you got to the n-1 reveal 🤣

[@Rodrigo-lq2iy]

Thank you very much! Really helpful content!

[@datatab]

Hello Rodrigo, many thanks for your Feedback! Cheers Hannah & Mathias

[@doof6416]

This was so helpful, thank you!

[@datatab]

Glad it was helpful! Regards Hannah

[@mehdi.sajadi]

thanks a lot, it was useful to deal with non-numerical variables

[@datatab]

Glad it helped!

[@nabuko4344]

thank you!

[@simjxin6696]

Both Chicago and NY have two coefficients, but are under one variable "Place". So what does the coefficients mean when inserted into the multiple regression equation?
I'm not sure if my question makes sense TT

[@muzahirahmednur5957]

Thanks so much! May Allah Almighty reward you with the best

[@datatab]

Thank you too for your comment! Regards Hannah

[@ryanbrink4074]

if there are three places of residence why do we only use two of them? Currently working on a MLR project and am struggling to understand which one to not include as I am using 4 indicator variables.

[@thatbengaligirl4559]

German for sure. Loved it!!!! :D

[@datatab]

No Austrian : ) Many thanks for you nice feedback, Regards Hannah

[@_Anonymous_9]

Thanks. How about if we have 2 categorical variables with 2 levels, and are also interested in an interaction term? (i.e. like a 2x2 ANOVA). What is the process for setting the dummy variables for the interaction term also?

[@datatab]

I am not quite sure, but would say it is done normally. So for both variables simply the categories 0 and 1 generate and for the interaction both multiply, then only 1 comes out if both are one!

[@_Anonymous_9]

@@datatab Thanks for your reply 😊. Yes that works. The problem comes with multi-collinearity after I add the (k-1) dummy variables of the interaction term into a model with the main effects. I can only add 1 level of the interaction term into the model without multi-collinearity problems, not (k-1).

[@JustineBoso]

Hi ! Thank you for the video it was very interesting and helpfull. I have a question, how many characteristics we can use for one variable ? Is there a limit ? Thank you !

[@asamijaz5459]

apart from goodness of presentation i really loved the accent aswell

[@datatab]

Many thanks : ) Regads Hannah

[@ASAM90]

@@datatab keep up the good work Hannah

[@datatab]

@@ASAM90 Many thanks : )

[@theforester_]

so just a quick question: if my dependent variable (y) is categorical i must perform logistic regression, however when my independent variable (x) is categorical i must create dummy variables.
is it correct ? sometimes i get confused by this. thanks! greetings from brazil

[@datatab]

Yes this is correct!!! Regards Hannah : ) Greetings from Austria

[@petercross1879]

@@datatab I need to make 2 box plots. 1 with systolic blood pressure for obesity, 1 for systolic blood pressure without obesity. I have no idea how to determine obesity with bmi of 30 or more.

[@aparajitaswami5509]

@@datatab But what should be done when both dependent and independent variables are categorical?

[@sleepless2541]

​@@aparajitaswami5509logistic regression

[@xxMegha33xx]

How to choose dependent and independent variable?

[@AlvinYakitori060]

How do we interpret coefficients of dummy variables with more than 2 values?

[@JOWIGAMINGGTA]

Can you perform a bivariate regression with only one dummy variable? How will this look like?

[@datatab]

Yes, for example, whether gender has an impact on salary! Then however the same results come out as if one simply computes a t test!

[@manifestationmaster1111]

If True == 1 in coding, shouldn't yes be 1 not 0?

[@SourovDattacse]

You have a friendly speaking style. Slow and Cute. Very helpful tutorial.

[@datatab]

Thank you! 😊

[@shahnawazusmani4035]

👍

[@datatab]

Thanks!

[@zupmutado5612]

kenal dr nizam ko?

[@datatab]

Sorry, understand only german or english : )

[@tronixlkelectronics8277]

1st

[@datatab]

2nd : )

[@ferry6700]

3rd

[@byongwook1]

4th

[@_Anonymous_9]

5th

[@nc375]

@@_Anonymous_9 6th 9ing on yo mamma

[@CreamyDrummer]

Ze reall germanzz

[@datatab]

Where are you from?

[@datatab]

Actually Austria : )

[@noellezoetormin1179]

HAHAHAHA this is the strongest German accent I've ever heard I love it

[@ASAM90]

Yes Austrian accent is very strong. I still remeber Brad Pitt having Austrian accent in 7 years in Tibet