- 88
- 4 359 680
R Programming 101
Ireland
Приєднався 31 жов 2018
This channel provides teaching videos on data analysis and statistical analysis using R programming. The teaching videos include subjects like data cleaning, data manipulation, data visualization, statistical analysis, and machine learning and AI (artificial intelligence).
Multiple regression analysis - effect modifiers and interactions
This is a video about linear regression and how when undertaking multiple regression analysis, we need to take into account the possibility of variables that interact and effect modifiers. Interaction and effect modifiers are important to understand when you are dealing with multiple variables in a complex dataset. This video walks you through the R programming skills you need to generate meaningful models.
Переглядів: 1 435
Відео
Multiple regression - making sure that your assumptions are met
Переглядів 1,7 тис.Місяць тому
Doing diagnostics on your model assumptions in R programming is easy. This video is about linear regression, specifically multiple regression and making sure that the assumptions of your model are met.
Multiple regression. How to deal with Outliers and Colliniarity
Переглядів 2,7 тис.3 місяці тому
When doing linear regression or multiple regression, your data may have outliers. Outliers are data points where the residual values are far from the model. In this video we explore how to identify outliers and discuss what to do when they are found. Colliniarity or multicolliniarity occurs when two or more of the explanatory variables are correlated. There are times when these variables should...
Simple Linear Regression.
Переглядів 3,9 тис.3 місяці тому
This is the fist in a series of videos that focus on Multiple Regression. Our starting point is to understand simple regression before building upon that understanding. Regression analysis considers the relationship between an explanatory variable and an outcome variable and allows us to understand how much of the outcome variable can be explained by the explanatory (or independent) variables. ...
Multiple regression: how to select variables for your model
Переглядів 5 тис.3 місяці тому
When doing linear regression, it is important to include right right variables in your model. Multiple regression differs from simple linear regression in that more than one explanatory variable is used in the model. Master variable selection in multiple regression with our concise guide! Dive into the art and science of choosing the right predictors for your statistical models. This video is p...
Adding variables to your multiple regression model
Переглядів 3,1 тис.4 місяці тому
Linear regression is considered to be simple regression if only one explanatory variable is used and multiple regression if the model includes more than one explanatory or independent variable. In this video we explore how to add additional categorical variables and numeric variable to your linear regression model. If you are interested in statistical analysis then learning how to undertake a m...
Multiple Regression from beginning to end in 30 minutes.
Переглядів 11 тис.5 місяців тому
Multiple regression is linear regression analysis using more than one explanatory variable. Regression analysis involves creating a model that can be used to predict the value of an outcome variable from an independent variable. This video uses R programming to to illustrate multiple regression and the diagnostics required to ensure that the assumptions are met. These include that the residual ...
Quarto - tips and tricks
Переглядів 4,2 тис.6 місяців тому
In this video about R programming Greg and Andrew (from Equitable Equations - see link below) talk through some tips and tricks when it comes to using Quarto in R Studio. Quarto is similar to R markdown but much more user friends. It allows you to create a finished document (word, PDF or slides) inside the R studio environment. So if you are into data analysis, data science, statistics or resea...
Lubridate - how to manipulate date and time data in R
Переглядів 9 тис.8 місяців тому
If you're learning R programming and want to manipulate data and time data then the lubridate package is going to rock your world. Its part of the tidyverse collecation of package and so integrates nicely with other tidyverse packages like ggplot2 and dplyr. Lubridate lets you parse strings into date and time objects, extract components of dates and times and even work with timeframes like dura...
Loops using R programming
Переглядів 11 тис.9 місяців тому
Loops are an important way to execute code in R programming that repeats itself. If you're interested in data analysis using R programming then this video about loops will be of interest to you. You'll be able to use loops to generate important insights from your data.
Quarto - replacing R Markdown in R Studio.
Переглядів 22 тис.9 місяців тому
Quarto - replacing R Markdown in R Studio.
Using R programming to manage categorial variables or factors using the forcats package
Переглядів 8 тис.Рік тому
Using R programming to manage categorial variables or factors using the forcats package
Ggplot Colors - how to use colors effectively when creating plots with ggplot2
Переглядів 7 тис.Рік тому
Ggplot Colors - how to use colors effectively when creating plots with ggplot2
Advanced ggplot #2 - create beautiful plots and graphs using R programming.
Переглядів 13 тис.Рік тому
Advanced ggplot #2 - create beautiful plots and graphs using R programming.
R programming for beginners: Select, filter and fill functions within the tidyverse
Переглядів 6 тис.Рік тому
R programming for beginners: Select, filter and fill functions within the tidyverse
Separate and Unite - manipulate your data with R programming
Переглядів 10 тис.Рік тому
Separate and Unite - manipulate your data with R programming
Group by and Summarise functions in R programming - use the tidyverse package to wrangle your data
Переглядів 27 тис.Рік тому
Group by and Summarise functions in R programming - use the tidyverse package to wrangle your data
Encircled observations - use ggplot and ggalt to create great plots and data visualization.
Переглядів 3,3 тис.Рік тому
Encircled observations - use ggplot and ggalt to create great plots and data visualization.
Doing a t-test using R programming (in 4 minutes)
Переглядів 55 тис.Рік тому
Doing a t-test using R programming (in 4 minutes)
Working with factors and categorical variables. Use forcats in R programming to change factor levels
Переглядів 20 тис.Рік тому
Working with factors and categorical variables. Use forcats in R programming to change factor levels
Excellent simplified explanation. Not everyone is gifted to teach but truly you are.
I always create a folder for each project and then create a new txt and finally change .txt to .R
Excellent!!
How do you get the friends.csv?
Question, I wasn't able to install Starwars in my R Studio. It said it wasn't available on my version of R. I have a MacBook Pro with a mac OS version of R. Does anyone have any solutions?
Nevermind. I was able to get it downloaded on my own so I can now follow along with this video
You're amazing at teaching this. Thank you!
Everything worked up to plot(). I get "Error in plot.default() : argument "x" is missing, with no default"
Thanks for this. Has the plot function completely changed since this video? I am getting an error message.
Great video
Really great
❤
Good videos and instructions, but I can't try anything without the data.
Thank you!🥺
Hello, Greg! Thank you for sharing this video! I have one question about the plots though - how did you display M on each density plot, and how did you manage to put the plots together?
Thank you sir ❤
Thanks for this awesome explanatory video
Thanks for these lectures
Thank you for teaching in such a clear and exciting way. I understood loops after months of trying
❤
I love how ChatGPT knows R Studio.
Gender and sex is now updated in the dataset. (gender in this video was what sex is now; female/male)
Thanks a lot for these tutorials.
I like your videos. You are the best teacher and you are practical in your teaching.
at 16:06 can you also arrange by name?
Hey Greg, love your video but PLEASE STOP THE SCRATCHING NOISES everytime you try to underline or point out something it nags me, idk if anyone's noticed but as a headphones users it feels like scratching with your nails on a chalkboard. Thank you.
Hey Greg, love your video but PLEASE STOP THE SCRATCHING NOISES everytime you try to underline or point out something it nags me, idk if anyone's noticed but as a headphones users it feels like scratching with your nails on a chalkboard. Thank you. 😅
This video is genuinely stellar. Is there a way we can download the R Script you used in this video?
very good lecture, really enjoyed it ! thanks a lot !
but the data says "sex" female/male and "gendeer" masculine/femenine".
Thanks a lot for this video! Very helpful!
Thank you for all this, But I can't see the PDF or any document to download, even after subscribing
Excellent...very helpful. I have one mor question ...on converting date into Week. Can you please send a video on this matter. Thank you in advance
Awesome video. Appreciate it. How can I get the cheat codes, tho?
Thank you Bro. It is fantastic and excellent. But I have a question how can i send ? My question is recoding or grouping using R for date converting them into Weeks for example from January 1-7 is week 1, January 8-14= week2 and etc ...
This is one of the best quick introduction tutorials I've ever seen. What a positive experience! Thank you for the video!
where can i get your source code can you please let me know.
Thank you. excellent. Very helpful.keep it up
How did you draw the graphs in the statistical analysis section? Starting from t-test all the way to linear model. Using the code I only saw outputs in the console.
really good video....but cant find the cheat sheet..:(
Excellent. Bro, I am always learning
Bro what ?! I am learning a lot. Thank you. Keep it up. Bless you.
Thank you so much! Please do logistic regression and ROC curve analysis soon.
Thank you so much for the great and useful videos
Are you South African?
thanks! could you share the code for this?
Super helpful and so easy to follow! Respect for the professor Greg!
Can someone explain the importance or interpret the F statistic in this video, value of 1433. I understand that the P value < alpha therefore the null hypothesis is rejected and there is a significant relationship between height and weight. Now, what does the F value add? what does an F value of 1433 mean?
ggplot 1
please where is pdf file .thank you
I am wondering the same thing.