Logistic Regression: An Introduction

Logistic regression is a special case of regression analysis and is used when the dependent variable is nominally scaled or ordinally scaled. This is the case, for example, with the variable purchase decision with the two characteristic values "buys a product" and "does not buy a product". Logistical regression analysis is thus the counterpart of linear regression, in which the dependent variable of the regression model must at least be interval-scaled. With logistic regression, it is now possible to explain the dependent variable or estimate the probability of occurrence of the characteristic values of the variable.

What is a logistic regression?
In the basic form of logistic regression, dichotomous variables (0 or 1) can be predicted. For this purpose, the probability of the occurrence of characteristic 1 (=characteristic exists) is estimated. In medicine, for example, a frequent application is to find out which variables have an influence on a disease. In this case, 0 could stand for not ill and 1 for ill and the influence of age, sex and smoker status on this particular disease is investigated.

More Information on logistic regression:

The Regression online calculator:

Regression Analysis: An introduction to Linear and Logistic Regression
Simple and Multiple Linear Regression
Assumptions of Linear Regression
Logistic Regression: An Introduction
Dummy Variables in Multiple Regression
Regression with categorical independent variables
Multicollinearity
Causality, Correlation and Regression

[romeojulyofficial]

After 10 hours trying to understand this concept, I'm finally found a solution here. Thank you a lot 👏

[anthonygikuri]

Thank you for this Innovation. I know many of us are lazy and tend to shy away from statistics but at least you made our life easy. I will share these videos with my students.

[DIRRON]

OMG THANK GOD FOR THIS VIDEO YOU MADE IT SO EASY TO UNDERSTAND FOR MY STATS EXAM

[trungtranang]

So ez to understand in 7 mins! thanks a lot

[chldhkstn]

The best youtube video I played in 2022.

[dr.linageorge]

Very well explained. Thanks a lot. I would like to know if a video could be made on regression analysis with multiple independent variables and multiple dependent variables. Specifically when a dependent variables have more than 5 items.

[jeanaimegakwerere]

Thank you so much for simplifying this, now it looks like drinking water

[frankstared]

Superb. Love the woman's voice, too.

[abigailwaimba]

After entering the independent and dependent variable, the answers are hidden.How can I use this logistic regression calculator?Should I download it ?

[asmassa]

Thank you for your video it’s amazing but can I use logistic regression of small sample size n=12?

[Jdonovanford]

Excellent and fun explanation. I would like to test if a series of continuous IV predict two categorical variables (income level and gender). As you see, the DV are two, one of them is binary (gender) and the other has several levels (low, medium, high, extreme). What type of regression shall I use? I considered bivariate logistic regression, but here one of the DV is not binary.

[Thath]

Ma'am can logistic regression use to find the impact of risk management strategies on company performance?

[MissyMossy]

Hi dear! Would like to ask you a question.
My DV is categorical- It is representative of whether participants committed <2 or >= 2 harsh accelerations during a drive.
My first IV is age (continuous)
My second IV is total sleep time in the 24 hours prior to the drive (continuous)
Example of how my data looks:
Participant ID/ Harsh accelerations/ Age(years) /Total time (mins)
1 2 42 500
1 5 42 540
2 6 23 620
2 2 23 450
2 2 23 420
3 1 31 200
3 11 31 280
3 4 31 340
3 1 31 360
In using a binary logistic regression (on SPSS) to examine whether driver age and total sleep time (TST) in the 24 hours prior to shifts had an impact on whether drivers would have <2 or ≥2 HA during drives, is it a problem if i have repeated age data as the same participant has contributed to 5 days worth of data for example? Will it solve the problem if i add participant(participant ID) as a variable in my model?

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