Hi Professor, First of all, I want to thank you for this course. It's really challenging to find R programming courses that focus on statistical analysis, so I truly appreciate it. I'm currently majoring in statistics and computer science and looking to advance my knowledge in both statistics and analysis. While working on the 2021 version of the course (I'm still on the first lecture), I discovered the 2022 version. I wanted to ask if the 2022 version is an upgrade of the 2021 course. Should I switch to the 2022 version, or continue with the 2021 one?
Hi Hector, both versions are essentially similar, the 2022 version has some improvements based on student feedback, but globally topics discussed are the same. You could just switch between lectures, e.g. after 2021 lecture 3, you could jump to 2022 lecture 4 without any issues.
Good day, Danny. I'm glad I came across your channel. I've been self-educating myself in the field of analytics (theory, sql, python, power bi, excel) since Jul 2022 using different ways and I'm certain this course will be a great addition, since I've already got used to basics in Python and find R is more attractive as a future data analyst. Your comprehensive approach by teaching others is really awesome! You taught people not only R functions itself, but you'd also covered the history, which I trully appreciate! My speaking/writing English aren't that good as reading/listening, because I seriously started learning English only in 2021 but I'm working on it. I was wondering if you could share your point of view about one question: do you think we can use R visualization in most cases or we'd retain Power BI instead to provide our reports to the stakeholders / team members? Cause I'm trying to figure out which one should I focus on as a future data analyst (but for me R seems more suitable and flexable rather than Power BI). Best wishes, Anton.
Thanks for the kind words, in my opinion R graphs are more suitable just because of the flexibility R provides. However, it really depends on how much time you want to invest in a single graph. In R a good visualization takes time and effort to make it in such a way that allows you to present it to a wide (non-expert) audience. Other graphing software has more sane defaults so that they look nicer, but end up limiting your creativity. In the end it's a trade-off, does your job offer the time to create a custom slick graphic in R which displays the data more accurately versus management wants/needs the default graph on its desk this Friday before the 2pm meeting with investors.
Hi Danny, I am curious to hear your professional opinion about how to fit a model that I find to be challenging. I have measurements of oxygen consumption taken at 4 different temperatures for 520 eggs belonging to 80 species of insects. The goal of my model is to look at how a series of predictors like location, mortality ecc. influence the slopes of the lines that describe the change in oxygen consumption across the 4 measurement temperatures. Oxygen consumption intuitively increases with egg mass, measurement temperature and age of the egg. What I do not understand is how to make these slopes the dependent variables. If I first make a model like oxygen~egg mass+age+measurement temperature and then I use the slopes for each species as dependent variable in a model like slopes~site+mortality+ambient temperature is that correct? Or is that discourage because I am doing statistics on statistics? Conversely, if I build only one model like oxygen~egg mass+age+measurement temperature+site+mortality+ambient temperature is this model actually looking at slopes? Sorry for the long question but I find it hard to get a reasonable answer by myself. Cheers
This seems really complex, since it's hard from the text to get a clear idea on what exactly your experimental setup is (given so many factors are involved). Feel free to send me an email (listed on the about page) so we can schedule a 1 hour zoom/teams meeting to go through your experimental setup and discuss what the best model for your data might be.
Thanks for the feedback. This was the one given to me by the university, I'm not a professional streamer but I'll do some tests to see if I can improve it.
Thank you, sir, for the excellent explanation.
Glad it was helpful! Thanks for leaving a comment.
many thanks. its very clear and comprehensive. Its great that you make it open and available for everyone
You're welcome, thanks for leaving a comment. Also check out the 2022 version of the lectures, the design is much slicker.
Hi Professor,
First of all, I want to thank you for this course. It's really challenging to find R programming courses that focus on statistical analysis, so I truly appreciate it.
I'm currently majoring in statistics and computer science and looking to advance my knowledge in both statistics and analysis. While working on the 2021 version of the course (I'm still on the first lecture), I discovered the 2022 version. I wanted to ask if the 2022 version is an upgrade of the 2021 course. Should I switch to the 2022 version, or continue with the 2021 one?
Hi Hector, both versions are essentially similar, the 2022 version has some improvements based on student feedback, but globally topics discussed are the same. You could just switch between lectures, e.g. after 2021 lecture 3, you could jump to 2022 lecture 4 without any issues.
I have little experience in programming and statistics, but I am interested in this course in order to go deep. thx
You're welcome, enjoy the lectures and thanks for commenting!
Thank you very much. I love the way you explain things. PERFECT!
Thanks so much for the compliment and taking the time to leave a comment.
Good day, Danny.
I'm glad I came across your channel. I've been self-educating myself in the field of analytics (theory, sql, python, power bi, excel) since Jul 2022 using different ways and I'm certain this course will be a great addition, since I've already got used to basics in Python and find R is more attractive as a future data analyst.
Your comprehensive approach by teaching others is really awesome! You taught people not only R functions itself, but you'd also covered the history, which I trully appreciate!
My speaking/writing English aren't that good as reading/listening, because I seriously started learning English only in 2021 but I'm working on it.
I was wondering if you could share your point of view about one question: do you think we can use R visualization in most cases or we'd retain Power BI instead to provide our reports to the stakeholders / team members? Cause I'm trying to figure out which one should I focus on as a future data analyst (but for me R seems more suitable and flexable rather than Power BI).
Best wishes,
Anton.
Thanks for the kind words, in my opinion R graphs are more suitable just because of the flexibility R provides. However, it really depends on how much time you want to invest in a single graph. In R a good visualization takes time and effort to make it in such a way that allows you to present it to a wide (non-expert) audience. Other graphing software has more sane defaults so that they look nicer, but end up limiting your creativity.
In the end it's a trade-off, does your job offer the time to create a custom slick graphic in R which displays the data more accurately versus management wants/needs the default graph on its desk this Friday before the 2pm meeting with investors.
@@DannyArends thanks a lot for your useful response! You improved my understanding in this concept!
It's very beautifully and usefully, sir! Thank you!
You are most welcome, thanks for taking the time to leave a comment !
very useful resource
thank you, im excited to learn more.
You're welcome, enjoy learning R
Great lesson.
Glad you liked it!
👏 👏 👏
A good job!
Many thanks for this
It says we will have n=13/14 lectures, but the playlist has 34 lectures. Is the playlist correct, Danny?
That is correct, every lecture (single theme) is 3 to 4 hours long, I recorded them in ~1 hour blocks due to coffee and smoke breaks.
@@DannyArends Oh! Thank you so much! :)
interesting
regards
Thanks for leaving a comment, R is an interesting language to learn
I had statistics, programing
R will be for you then, combining stats, programming, and data visualization
Hi Danny, I am curious to hear your professional opinion about how to fit a model that I find to be challenging. I have measurements of oxygen consumption taken at 4 different temperatures for 520 eggs belonging to 80 species of insects. The goal of my model is to look at how a series of predictors like location, mortality ecc. influence the slopes of the lines that describe the change in oxygen consumption across the 4 measurement temperatures. Oxygen consumption intuitively increases with egg mass, measurement temperature and age of the egg. What I do not understand is how to make these slopes the dependent variables. If I first make a model like oxygen~egg mass+age+measurement temperature and then I use the slopes for each species as dependent variable in a model like slopes~site+mortality+ambient temperature is that correct? Or is that discourage because I am doing statistics on statistics? Conversely, if I build only one model like oxygen~egg mass+age+measurement temperature+site+mortality+ambient temperature is this model actually looking at slopes? Sorry for the long question but I find it hard to get a reasonable answer by myself.
Cheers
This seems really complex, since it's hard from the text to get a clear idea on what exactly your experimental setup is (given so many factors are involved). Feel free to send me an email (listed on the about page) so we can schedule a 1 hour zoom/teams meeting to go through your experimental setup and discuss what the best model for your data might be.
Great. I just sent you an email. Thanks. @@DannyArends
Good god, an hour before we start talking R :) 🙂
Education is all about embedding and providing context 😉
Would be nice to start this course with someone else.looking for accountability partner
That is a good idea, to have someone to keep you on track.
I am a statistician
Welcome to the channel, enjoy learning R
great to be here, may i be guided on how to reach out to you
Just drop me an email, it's on the about page of my UA-cam channel.
Wish you could use a different mic. It's hard to hear with the speaker.
Thanks for the feedback. This was the one given to me by the university, I'm not a professional streamer but I'll do some tests to see if I can improve it.
how could i access your email pls
My email is on the about page of my channel.
can i have your email please
Sure, it's on my about page, but danny.arends@gmail.com