Published 10/2023
Created by EDUCBA Bridging the Gap
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 14 Lectures ( 1h 41m ) | Size: 591 MB
Learn Logistic Regression in the simplest way using python and a case study
What you'll learn
Know in detail about regression analysis
Develop a logistic regression model using python
Learn how to interpret the modeling results and present it to others
Know about the different methods of finding the probabilities
Requirements
python basics
Statistics basics
Description
Uses of regression analysisRegression analysis helps to find the significant relationship between dependent variable and independent variableIt helps to know the amount of impact caused by multiple independent variables on a dependent variableIt helps to compare the effects of variables measured using different scales. This comparison will help to bring out the best to be used for predictive modelling.Regression analysis is used in businesses for a lot of reasons like to find out the factors responsible for business profit, to forecast the future value, to know how the interest rates can affect the stock price and so on.Regression analysis is used as a quantitative research method which is used when the research involves modelling and analysis of several variables.This course offers theoretical and practical training for researchers, statisticians and other professionals with particular emphasis on logistic regression model. This is a course where freshers can become an expert at using Python to analyze binary response data using logistic regression. There are many practical examples and case studies given in this course which will help you to learn better. After taking this course you will become a more confident user of python to compute logistic regression. Regression analysis is a form of predictive modelling technique which helps to determine the relationship between dependent and independent variable. It helps to find out the average value of the dependent variable when the independent variables are fixed. This chapter explains in detail about regression analysis and it also includes the areas of application of regression analysis, types of regression, regression models, assumptions of regression analysis and about Interpolation and Extrapolation.
Who this course is for
Anyone who is interested in modeling data and estimate the probabilities of given outcomes.
Homepage
https://rapidgator.net/file/17842a85b4c528664c3d22eef2d8cc9c
https://ddownload.com/deapz6l34j0r
