Introduction to Regression with statsmodels in Python

Starting at USD 39.00
4 hours duration

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

This course focuses on utilizing Python statsmodels for linear and logistic regression, two widely used statistical models. By mastering these models, you will gain the ability to uncover valuable insights hidden within your data. Throughout the course, you will engage in hands-on exercises that explore the relationships between variables in various real-world datasets, such as motor insurance claims, Taiwan house prices, and fish sizes. The course begins by providing a comprehensive understanding of regression, highlighting the differences between linear and logistic regression, and teaching you how to apply both models effectively. You will also learn how to utilize linear regression models to make accurate predictions and comprehend model objects. As you progress, you will delve into assessing the fit of your models and determining the effectiveness of your linear regression model. Additionally, you will explore logistic regression models in greater detail, enabling you to make predictions using real data. By the end of this 4-hour course, you will have acquired the necessary skills to make predictions, evaluate model performance, and diagnose issues related to model fit. You will have a solid grasp of Python statsmodels for regression analysis and the ability to apply these skills to real-life datasets.

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Online Education Provider ยท 410 courses
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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