Sonja_Janssen
Sonja Sahebzad
Recently Published
Urban Air Quality Explorer: Shiny Application Pitch
Five-slide RStudio Presenter pitch for the Johns Hopkins University / Coursera Developing Data Products course project. It presents the Urban Air Quality Explorer Shiny application, its interactive features, model comparison, and limitations. Created by Sonja Sahebzad on September 17, 2026.
What Shapes Urban Air Quality? - Interactive Plotly Presentation
An interactive R Markdown presentation exploring urban air quality with Plotly. It includes interactive charts, interpretations, limitations, visible slide navigation, and the creation date.
Amsterdam: A Data Scientist’s City Guide
An interactive Leaflet map created in R Markdown featuring selected learning, cultural, and green locations in Amsterdam. The map includes clickable markers, informative pop-ups, a legend, thematic layers, and API-free OpenStreetMap tiles.
Amsterdam: A Data Scientist’s City Guide - Interactive Leaflet Map
An interactive city guide created by Sonja Sahebzad using R Markdown and Leaflet. The map highlights selected learning, science, cultural, and green locations in Amsterdam with colour-coded markers, informative pop-ups, a legend, and selectable map layers.
Predicting Barbell-Lift Execution from Wearable Sensors
Practical Machine Learning course project by Sonja Sahebzad. A random forest model was developed using five-fold cross-validation to predict barbell-lift execution from wearable-sensor data. The report includes preprocessing, model evaluation, expected out-of-sample error, discussion, conclusions, and predictions for 20 test cases.
Transmission Type and Fuel Economy: An Analysis of the mtcars Data
A regression analysis of the mtcars data examining whether manual or automatic transmission is associated with better fuel economy and quantifying the adjusted MPG difference.
Severe Weather in the United States: Health and Economic Impacts
Analysis of NOAA storm data for Course Project 2 in Reproducible Research. The report compares fatalities, injuries, and property and crop damage, and includes R code, two figures, limitations, and a conclusion.
Reproducible Research Analysis: Activity Monitoring Data
The assignment involves addressing 5 key questions related to processing and analyzing “activity monitoring data.” This data analysis project revolves around the exploration of activity monitoring data collected over two months. The dataset originates from a study in which an individual used a personal activity monitoring device to track daily step counts at five-minute intervals. The dataset includes variables such as steps taken, date, and time intervals.