Logistic Regression Basics Explained: Probabilities, Odds, Odds-Ratios and Log-Odds-Ratios (4K)

IF YOU WOULD LIKE TO SUPPORT, PLEASE JOIN THE CHANNEL: / @yuzar-data-science
IF YOU WANT JUST RAW R CODE PLEASE JOIN THE CHANNEL AND ASK ME TO POST A CODE ON THE COMMUNITY SPACE: / @yuzar-data-science
Enjoy! 🥳
Welcome to my VLOG! My name is Yury Zablotski & I love to use R for Data Science = "yuzaR Data Science" ;)
This channel is dedicated to data analytics, data science, statistics, machine learning and computational science! Join me as I dive into the world of data analysis, programming & coding. Whether you're interested in business analytics, data mining, data visualization, or pursuing an online degree in data analytics, I've got you covered. If you are curious about Google Data Studio, data centers & certified data analyst & data scientist programs, you'll find the necessary knowledge right here. You'll greatly increase your odds to get online master's in data science & data analytics degrees. Boost your knowledge & skills in data science and analytics with my engaging content. Subscribe to stay up-to-date with the latest & most useful data science programming tools. Let's embark on this data-driven journey together!

[@zhakota1979]

Thanks a lot for the guidance! The most understandable explanations of statistics.

[@yuzaR-Data-Science]

That's so nice of you! Appreciate that! Hope the rest is useful too. Kind regards!

[@amosarubi8468]

Thanks. Your videos and perspective are unique.

[@yuzaR-Data-Science]

I appreciate that! Hope they are useful too ;) Thanks for watching!

[@ChiMickE]

Well explained, thank you!

[@yuzaR-Data-Science]

Glad it was helpful! Thanks for watching!

[@Inexorablehorror]

Many thanks. Could you please also do something about probit regression (and as compared to logit regression), as well as ordinal probit regression? Many thanks for your effort!

[@yuzaR-Data-Science]

Great suggestion! You are actually not the first who asked for it. So, this video is now very high in the rankings! Thus, please, stay tuned. And thanks for watching and commenting! 🙏 That's the best support!

[@soylentpink7845]

Again, great video!!

[@yuzaR-Data-Science]

thanks for positive feedback and for watching! 🙏

[@yaoliao3517]

Thanks. I watched every video.

[@yuzaR-Data-Science]

You rock! Thanks for watching and commenting that's the best support! Sorry, that they aren't more frequent. I have a day job and at the same time try to maximize the quality of content.

[@45tanviirahmed82]

Sweet problem while watching your videow is: I try to link it with all other videos you've uploaded and I get lost 😆 Solution: I again watch that specific video of yours where I think I got lost and get back on track. the best thing about your videos is every second is informative. Thank you very much.

[@yuzaR-Data-Science]

Thats so nice of you! Thanks a lot for noticing and communicating "every second is informative" to me! I try not to waste time of viewers but I was not sure it worked. Thanks for watching!

[@ibrahimlawan418]

Thanks a lot

[@yuzaR-Data-Science]

Most welcome!

[@user-vr5de5rt9f]

How I understood what odds are, odds ratios. Using your example: the survival rate of females on a ship is 70 to 30, males 20 to 80. If we convert it into probability, then for females it is 0.8, and for males 0.2. How to calculate the odds based on this probability: chance (to survive) = probability (of survival) / (1 - probability (of survival)) = 0.7 / (1-0.7) = 2.33. It turns out that females have a chance of survival that is 2.33 times greater than the chance of dying. According to this formula, men have a chance to survive = 0.25, that is, the chance to survive is 4 times less than the chance to die. Or if you can interpret the odds this way - for every 233 surviving females, there are 100 dead. For every 25 surviving males, there are 100 dead. Odds ratio, as I understand it, calculates the odds ratio for two events, let’s assume event A - female survival rate is 70% and event B - male survival rate is 20%. Formula Odds ratio = Odds females (2.33) / Odds males (0.25) = 9.32. OR = 9.32 means that the chances of a female surviving a given event are 9.32 times greater than the chances of a male surviving the same event.

[@yuzaR-Data-Science]

Yes 👍 your intuition is correct ✅

[@IbrahimKwakuDuah]

Excellent video

[@yuzaR-Data-Science]

Thanks Ibrahim!

[@Endrumpf]

Prof. Please increase the frequency of videos. All forms of Probit Model, Impact evaluation model like Switching regression, DID, and so on...

[@yuzaR-Data-Science]

Thanks for your positive comments! I would love to increase the frequency, but I still have a day job. One thing what makes me work more on these videos, is the growing number of members. Thus, feel free to join the channel. Also, watching, liking, commenting and sharing helps to grow. Thus, if you feel like doing any of this, it would help me grow and I'll increase the frequency of posting. Cheers

[@Endrumpf]

@@yuzaR-Data-Science Surely Prof. Thanks for the reply.

[@yuzaR-Data-Science]

@@Endrumpf you are very welcome!