Intermediate Regression in R

Mathematics and Statistics

Short Description

Learn to perform linear and logistic regression with multiple explanatory variables.

Long Description

Linear regression and logistic regression are highly popular statistical models that serve as powerful tools for uncovering valuable insights within datasets. This comprehensive course expands upon the foundational knowledge acquired in the Introduction to Regression in R course, delving into the intricacies of linear and logistic regression with multiple explanatory variables. Through engaging hands-on exercises, participants will have the opportunity to analyze the intricate relationships between variables within real-world datasets, such as Taiwan house prices and customer churn modeling. By the conclusion of this course, attendees will possess the expertise to effectively incorporate multiple explanatory variables into their models, comprehend the impact of variable interactions on predictions, and gain a thorough understanding of the underlying mechanisms of linear and logistic regression.

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Course Details

Duration: 4 hours
Difficulty: Advanced
Format: Short Course
Price: USD39.00
Course Link

DataCamp

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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