Logistic Regression [Simply explained]

[@datatab]

If you like you can download our free Logistic Regression Playbook: datatab.net/tutorial/statistics-playbook 🙂

[@tomyanggriawan7534]

Thankyou

[@MrAbah105]

simple explanation, thanks

[@parulbhaiya5158]

This is the best and the easiest method of explanation so far I've seen for the particular topic. Thankyou!!!

[@allemagallied4775]

13:49 is a mistake I think. odds ratio of 1.04 does not mean that the probability increases by 1.04 times. An odds ratio of 1.04 means that for a one-unit increase in the independent variable, the odds of the event happening (in the context of a binary outcome) are 1.04 times higher. It does not directly relate to a specific change in the probability of the event occurring. To understand the impact on probabilities, you would need to convert the odds ratio back to probabilities using the logistic function. The mistake is in confusing odds and probabilities.

[@user-zz4xf5mq9p]

Yup, this is correct. Good catch!

[@eyesabroad]

you are right !!!

[@md.kutubulalamubayed6205]

I love the way you deliver your lecture ... its superb. many many thanks

[@CuradoDAvena]

After a long hiatus from statistic, your videos have helped to put me up to speed. This one in particular, was excellent! Thank you

[@ahmadneri5602]

I want to give you 1000like because it was a best video and explain. It was very helpful I learned it all of them

[@datatab]

Many thanks : )

[@rawiahnaoum4382]

You explain it very well. It is like 1+1 =2 -- it is really easy to understand

[@datatab]

Many thanks : )

[@J2C1983]

This is an excellent explanation of logistic regression! Very easy to follow! Thanks!

[@datatab]

Glad it was helpful!

[@muhammedhadedy4570]

Amazing tutorial and amazing statistical software. Thanks so much for your great videos. Please, keep up the great work.

[@datatab]

Thanks, will do! Many thanks for your nice Feedback!!! Regards Hannah

[@PremBankerVT]

i love this video. The concept is explained in a very easy manner

[@datatab]

Many thanks!

[@pushkal8800]

I have one doubt , is logistics regression = sigmoid(linear regression) or are there any other differences. Other than that amazing video, never found this much clarity.

[@datatab]

@@pushkal8800 Yes, logistic regression is essentially a combination of linear regression followed by the application of a sigmoid function. However, while this captures the essence of how logistic regression models the relationship between the independent variables and the dependent variable, there are a few more nuances that distinguish logistic regression from simply applying a sigmoid function to linear regression.

[@jwoluenpao]

Thank you. That was the first time for me to understand what logistic regression was. It really helps.

[@Vladimir-Marin]

You made it so easy, thank you ☺

[@familians]

You could lime this video too: Another great video about logistic regression in JMP kzbin.info/www/bejne/b6qxkKygfKZ9kKcsi=jUwEZUDobBudE8AE

[@antonrosenfeld6861]

Thank you this was explained extremely clearly with practical examples, I now understand all the concepts.

[@pirdrmuhammadrafiqshah9452]

So nice, intresting and helpful. Thank You so Much. !

[@MrCEO-jw1vm]

Great one. I got a nice understanding of this concept

[@datatab]

Glad it was helpful!

[@fabio.s.barbosa]

thanks a lot for your explanation. Easy to follow and very instructive.

[@datatab]

Thanks : )

[@markleeismylee1511]

Ma'am, you are my hero😍

[@muhammadfaisyalalauddinmuk6646]

That was sooo clear. Thank you for the video

[@datatab]

Glad it was helpful!

[@atharvigupta4250]

very good and clear explanation, thank you

[@datatab]

Glad it was helpful!

[@laminaung2444]

Thanks. A very comprehensive explanation.

[@ThomasHaberkorn]

Yet again a great video, thanks 👍

[@datatab]

Thank you Thomas and thank you for your feedback!!!! : )

[@DailyMeditation365]

Amazing video that really helped me understand logistic regression better. Thank you!

[@temib9077]

Fantastic presentation

[@DanielRamBeats]

This is a beautiful example, thank you. You guys should do one on neural networks

[@FlashPodzz]

You guys made it simple and clear 😁

[@datatab]

Thanks!

[@oceanview3165]

She sounds so much like my physics professor from Ukraine! Excellent explanation!

[@muchazmuchaz2885]

Best video ever. Thank you

[@johannasteinbock1848]

Min 8:12: What does "correctly assigned" mean in this context?

[@Featherlicht]

Lovely explanation ❤

[@zunaidqureshi8521]

Thanks for this wonderful explain!

[@datatab]

Glad it was helpful!

[@abcdefghijkl5412]

Too many thanks. It's very well explained and understood. May you help and also make a detailed video on ordinal logistic regression and multinomial logistic regression, explaining the different equations used under each step by step like you have done under binary logistic regression? Thanks

[@datatab]

Hi many thanks for your feedback! Yes it is on our to do list but it will certainly still take a while!! Regards Hannah

[@shamanahuji]

very nice video. very well explained. Thank you

[@Stargazerr29]

Thank you for this!

[@datatab]

Many thanks : )

[@risausa4796]

Thanks for this video!

[@dees900]

Great class. thank u

[@sattyajitdatta9109]

Excellent!

[@hayleyk70]

Hi, Sorry if this is a daft question, I'm new to this methodology, is multiple logistic regression in research considered primary research?

[@isurusenevirathne]

well explained

[@DesalegnTesfaye-u9v]

no vedio on the curve ,no link?

[@mahnoormukhtiar9072]

0.28,o.03 are less than 0.05 but you said in our observation that no value is less than 0.05, so there is no independent variable with a significant influence. in the chi^2 test, while explaining the difference between model , you said dependent variables are used in the logistic function. while we use independent variable. Could you consider these suggestion?

[@ntelekoamasiane9817]

If I am dealing with ordinal data as independent variables on a Likert scale in logistic regression, then what will be my reference value for the independent variables? Which one do I choose from disagree, neutral or agree? Because under dependent variables I understand I will choose 'agree'

[@rizkyfadhillah4295]

If we use a binary logistic regression test, should the independent variable be made into two categories? Can't we analyze it if the independent variable has more than two categories? Especially if the two independent variables are in ordinal data form and the dependent variable is in nominal data form.

[@yusufxanderortega5944]

how do we determine the coefficient parameters in model?

[@antonellaorologiaio5383]

How can I add control variables in DataTab?

[@dr.battulapradeep1183]

No video on ROC curve. If available provide link.

[@datatab]

Sorry! Now it is there: kzbin.info/www/bejne/h3O5q414qM6ZaJI

[@zudimunir7798]

good video

[@robertapereira7896]

Great video, congrats! Do you perhaps have a video on probit analysis (including 0 and 100% values in the dataset)? Thank you very much.

[@Raya7766]

Thank you but you didn't mention what r square means in logistic regression. You just said that it's different.

[@bladongarland8635]

I feel like the use of the word dichotomous was simply to sound cool. Considering logistic regression is often used in computer programs, I think binary would have been much more suitable of a term. Feel free to educate me on why dichotomous was used if it is a better term.

[@TheLoneWanderer19]

I think dichotomous is used to align with the existing and established name of a type of categorical variable in statistics in general; in this case, a dichotomous variable/data. While logistic regression may be often used in computer programs, its application actually transcends to varied fields especially in business and marketing, social science, and public health.

[@homaanrandm9441]

If I give you a dataset, can you help me with Rcodes

[@Easynimics]

Just loved you..

[@abdremo]

well explained, thank you, btw you can pronounce dichotomous as die-cut-o-mus

[@datatab]

Hi, many many thanks for your feedback! Thant helped me a lot : )

[@emmanuealcabanig6263]

Max COllins myghadddd ,, parang Miss Universe

[@rupeshkamble9105]

Thanks the video

[@tsadikusetegn9345]

you are so cute ! Thank you so much for making it very easy for us

[@jignashasoni2129]

Wrong. In logistic regression, the response variable is an attribute variable that can be binary, nominal, or ordinary. you were only talking about the binary response variable.

[@temib9077]

She is not wrong, the explanation is as good as one can get in a short video, of course, the response variable is the dependent variable, and for the binary she is right, and that is what the video is all about.

[@aybeeaa8662]

Damn man this is so confusing 😢

[@familians]

Hi!! Try this one… you may like: Another great video about logistic regression in JMP kzbin.info/www/bejne/b6qxkKygfKZ9kKcsi=jUwEZUDobBudE8AE