Week 9

A course in RStudio/Shiny 

What have you learnt?

As we reflect upon our experience with RStudio and Shiny for statistical topics, we are amazed at the immense power and flexibility these tools offer in the field of data analysis. RStudio, with its integrated development environment, provides a seamless workflow for statistical programming, while Shiny allows for the creation of interactive web applications to showcase statistical insights. Together, they have revolutionized the way statisticians and data scientists communicate their findings.

One statistical topic that stands out in our minds is exploratory data analysis (EDA). With RStudio, we were able to quickly import datasets, visualize distributions, and identify patterns and outliers. For instance, when analyzing a dataset of housing prices, we used RStudio's ggplot2 package to create informative histograms, box plots, and scatter plots. Shiny then allowed us to build an interactive web application where users could dynamically explore the relationships between variables and gain deeper insights into the housing market dynamics.

Another topic where RStudio and Shiny truly shine is hypothesis testing. RStudio's vast collection of statistical packages, such as stats and dplyr, enabled us to perform various tests, including t-tests and chi-square tests. We recall working on a project examining the effectiveness of a new drug treatment. By leveraging Shiny, we developed a user-friendly interface that allowed researchers to input their own data, select the appropriate test, and visualize the results through interactive plots and summary tables.

In conclusion, RStudio and Shiny have been invaluable companions in our statistical journey. Their seamless integration, extensive libraries, and interactive capabilities have enhanced our ability to explore data, conduct rigorous analyses, and effectively communicate statistical insights. Whether it's EDA, hypothesis testing, or any other statistical topic, these tools have consistently proven their worth, empowering us to tackle complex problems and make data-driven decisions with confidence.

Group Task 1:  Learning RStudio/Shiny during the class