Data Management and Statistical Analysis with R

Raw data is only valuable if you know how to interpret it and turn it into actionable insights. This course provides a solid foundation in data literacy, teaching you how to classify information, summarize it accurately, and perform rigorous analysis using R. You will move from understanding basic data types to performing complex statistical evaluations. By the end of this course, you will be able to transform messy datasets into clear, numerical, and written summaries that drive informed decision-making. What you'll learn: - Classify different types of data to ensure correct analytical approaches - Calculate and interpret descriptive statistics to summarize key data features - Apply modern R programming techniques and Tidyverse principles for data manipulation - Understand and utilize common probability distributions in statistical modeling - Analyze sampling distributions and account for sampling errors in your findings - Practice data integrity and ethical considerations in modern data management The curriculum begins with core terminology and data classification before moving into practical statistical summaries and probability theory. You will progress through detailed written explanations and sharpen your skills with structured code-based exercises. This course is designed for beginners who want to build a strong analytical foundation without any prior experience in statistics or programming. Start building your data analysis skills today.