Applied Statistics and Data Analysis with Excel and R

Understanding data is no longer optional in a world driven by information. This course provides a clear path to interpreting numbers and making sense of complex datasets without needing a heavy mathematical background. You will transition from basic concepts to confidently performing statistical tests and analyzing trends using industry-standard tools. The course focuses on practical application, ensuring you can apply these skills to real-world datasets immediately through written explanations and code-based exercises. What you'll learn: - Understand core statistical concepts including probability, distributions, and hypothesis testing - Perform descriptive and inferential analysis using modern Excel functions and dynamic arrays - Apply data manipulation and visualization techniques within the R environment using the tidyverse - Interpret p-values, confidence intervals, and regression models to draw meaningful conclusions - Practice cleaning and preparing raw data for analysis to ensure accuracy and reliability - Analyze real-world scenarios to solve business and research problems through statistical evidence The content begins with essential terminology and foundational definitions before guiding you through practical applications in both Excel and R. This structured approach ensures you build a solid theoretical base while gaining hands-on experience with data through reading and written practice. This course is designed for absolute beginners who want to learn data analysis from the ground up, with no prior experience in statistics or coding required. Start building your analytical skills today.