Handling Missing Data with Imputations in R

Social Sciences

Short Description

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Long Description

Missing data is a pervasive issue that requires effective solutions for accurate predictions and to stand out from others. This course focuses on the skill of imputation, which involves filling in missing values correctly. Through this course, you will acquire the knowledge of utilizing visualizations and statistical tests to identify patterns in missing data. Additionally, you will learn how to impute data using a range of statistical and machine learning models. The course also emphasizes the development of decision-making abilities to determine the most suitable imputation method for specific scenarios. Furthermore, you will be taught how to incorporate the uncertainty resulting from imputation into your inference and predictions, enhancing their robustness and reliability.

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Course Details

Duration: 4 hours
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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