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# Case study logistic regression models

First off, the name is a misnomer. Classification refers to a predictive model where a class label is predicted for a given example of input data. The nurse, Shizune, wants to find out the amount of damaged cells in his brain, so she performs an MRI. This is a classification problem as we try to predict a class label for the given input.

## Get Started - A predictive modeling case study

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course Course 2 to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations. This course will introduce and explore various statistical modeling techniques, including linear regression, logistic regression, generalized linear models, hierarchical and mixed effects or multilevel models, and Bayesian inference techniques. All techniques will be illustrated using a variety of real data sets, and the course will emphasize different modeling approaches for different types of data sets, depending on the study design underlying the data referring back to Course 1, Understanding and Visualizing Data with Python. This course utilizes the Jupyter Notebook environment within Coursera. Awesome overview about what can we do with statictics knowlegde!

### Logistic regression in case-control studies: the effect of using independent as dependent variables

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Retention analysis based on a logistic regression model: A case study Abstract: Telecommunication data has provided new opportunities for both businesses and academia to analyze subscribers' behavioral patterns. Recently, there have been many changes in this industry, i.

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