Statistics with R (1) – Linear regression

In this video, I show how to use R to fit a linear regression model using the lm() command. I also introduce how to plot the regression line and the overall arithmetic mean of the response variable, and I briefly explain the use of diagnostic plots to inspect the residuals. Basic features of the R interface (script window, console window) are introduced.

The R code used in this video is:


#[1] “Ozone” “Solar.R” “Wind” “Temp” “Month” “Day”


#calculate mean ozone concentration (na´s removed)


#use lm to fit a regression line through these data:






Paul S says:

Thanks a ton, ur awesome

Oleksandr Sholin says:

Thank you very much, everything works pretty well, now I understand at least some stuff in R.

JWAN ALI says:

thank you

flamboyant person says:

Hello, please come back and make more vidoes on R we really need you Sir.

Prof Nandish Patel says:

Thank you Christoph! Excellent introduction to R. Simiplicity is most effective for learning. :)

Laura Lorenzo says:

This is great!! Now I have a much better idea of what I’m doing in R. Thank you very much!!


Sir, Please post the tutorial for user defined function for Simple Linear Regression in R without using any R packages or library.

HJ Kim says:


Roshan Fernando says:

Does anyone have any experience with Version 3.3.0? I am having trouble with the “control R” part and calling data…

Drzhivago11 says:

Very nice! Good job..

Erwan BUREL says:

Many thanks Mr Scherber.


A very helpful video for me! Thanks a lot Mr. Scherber. Please would you mind helping me with K-Fold Cross-validation (k = 10) or LOOCV or Validation Set Approach? How to use them to perform regression models, specifically the -kFold CV?

Vimal Raj says:

perfect for beginners.. i appreciate your work

Charles Rambo says:

Thank you!

Helmut Dittrich says:

Awesome, thank’s a lot. Very helpful

Charlie says:

I don’t have the data sets

Samukeliso Dlamini says:

After writing data which button u press to pops up data set range plz help me???????

Rebecca Liu says:

Thanks a lot, this is really easy to follow.

Jibreel Ahmad says:

woow! what an incredible tutorial. This the best, I really appreciate your work Christoph :-)

KnorpelDelux says:

Super Video, vielen Dank aus Bayern!

Oluwagbenga Aremu says:

thank have really been of great help to me

Er Td says:

Very helpful tutorial. Any tips on sourcing data directly from an excel spreadsheet(s) to run regressions in R?


Easy and good starting point on R

radiazione cosmica di fondo says:


SagarmathaSipahi says:

I am sure this is a great tutorial but in my case when I use the plot command, it keeps on saying object ‘Ozone’ not found (Please help, if possible):

My editor: data(airquality)
#Ozone” “Solar.R” “Wind” “Temp” “Month” “Day”
plot(Ozone,Solar.R, data=airquality)

My R Console
> data(airquality)
> names(airquality)
[1] “Ozone” “Solar.R” “Wind” “Temp” “Month”
[6] “Day”
> plot(Ozone,Solar.R)
Error in plot(Ozone, Solar.R) : object ‘Ozone’ not found
> plot(Ozone,Solar.R, data=airquality)
Error in plot(Ozone, Solar.R, data = airquality) :
object ‘Ozone’ not found

Junrui Zhang says:

This video is extremely helpful! Thanks a lot! Can I have anther question for you? Assume I have 3 columns. Id,price and date. I want to run regression model between price and date, but under the condition that they have the same id. In another word, I want to see all the regression result that are grouped by different id. What codes should I put there? Wish you could help me! Thanks a lot!

Denis Gris says:

Great lesson ….thank you very much

Dominique Barrette says:

Truly informative, thank you, you explain so well

Nigel Jacobs says:

Thanks so much!

Charles Silber says:

Very very helpful in explaining linear regression. Thank you.

Write a comment


Human Verification: In order to verify that you are a human and not a spam bot, please enter the answer into the following box below based on the instructions contained in the graphic.

Do you like our videos?
Do you want to see more like that?

Please click below to support us on Facebook!

Send this to a friend

▷ Other ReviewsVehicles▷ Show Cars▷ Motorbikes▷ Scooters▷ Bicycles▷ Rims & Tires▷ Luxury BoatsFashion▷ Sunglasses▷ Luxury Watches▷ Luxury Purses▷ Jeans Wear▷ High Heels▷ Kinis Swimwear▷ Perfumes▷ Jewellery▷ Cosmetics▷ Shaving Helpers▷ Fashion HatsFooding▷ Chef Club▷ Fooding Helpers▷ Coktails & LiquorsSports▷ Sport Shoes▷ Fitness & Detox▷ Golf Gear▷ Racquets▷ Hiking & Trek Gear▷ Diving Equipment▷ Ski Gear▷ Snowboards▷ Surf Boards▷ Rollers & SkatesEntertainment▷ DIY Guides▷ Zik Instruments▷ Published Books▷ Music Albums▷ Cine Movies▷ Trading Helpers▷ Make Money▷ Fishing Equipment▷ Paintball Supplies▷ Trading Card Games▷ Telescopes▷ Knives▷ VapesHigh Tech▷ Flat Screens▷ Tech Devices▷ Camera Lenses▷ Audio HiFi▷ Printers▷ USB Devices▷ PC Hardware▷ Network Gear▷ Cloud Servers▷ Software Helpers▷ Programmer Helpers▷ Mobile Apps▷ Hearing AidsHome▷ Home Furniture▷ Home Appliances▷ Tools Workshop▷ Beddings▷ Floor Layings▷ Barbecues▷ Aquarium Gear▷ Safe Boxes▷ Office Supplies▷ Security Locks▷ Cleaning ProductsKids▷ Baby Strollers▷ Child Car Seats▷ Remote ControlledTravel▷ Luggages & Bags▷ Airlines Seats▷ Hotel Rooms▷ Fun Trips▷ Cruise Ships▷ Mexico Tours