Data Analytics & Reporting
Learning Outcomes
This module equips participants to interpret and summarize analytical patterns in a clear and responsible way. Participants explore how to identify meaningful patterns in data, avoid overreach or misinterpretation, and understand the limits of what analysis can support. Emphasis is placed on producing analysis that is ethically sound, analytically grounded, and appropriate for the intended audience, supporting the creation of clear reports and presentations.
Learning outcome one
Build comfort identifying and summarizing analytical patterns.
Learning outcome two
Learn to avoid overreach or misinterpretation of analytical patterns.
Learning outcome three
Equip participants to build reports or presentations that are audience-appropriate, ethically clear, and analytically grounded.
Course Content
5.1 – AR – Asking Questions
5.2.1 – AR – Non-Technical Aspects of Data Work – Data in the News
5.2.2 – AR – Non-Technical Aspects of Data Work – Roles and Responsibilities
5.2.3 – AR – Non-Technical Aspects of Data Work – Multiple I
5.2.4 – AR – Non-Technical Aspects of Data Work – Analysis Cheat Sheet
5.3 – AR – Quantitative Skills and Tools
5.4.1 – AR – Data Analytics – Poisonous Mushrooms
5.4.2 – AR – Data Analytics – Data, Objects, Attributes, Modes
5.4.3 – AR – Data Analytics – Workflows and Pipelines
5.5.1 – AR – Data Analysis – Basic Analysis Methods
5.5.2 – AR – Data Analysis – Data Wrangling
5.5.3 – AR – Data Analysis – Data Cleaning
5.5.4 – AR – Data Analysis – Invalid Entries
5.5.5 – AR – Data Analysis – Missing Observations
5.5.6 – AR – Data Analysis – Outliers and Anomalous Observations
5.5.7 – AR – Data Analysis – Data Transformations
5.5.8 – AR – Data Analysis – Dimension Reduction
5.6.1 – AR – Evaluating Outcomes – GoC Framework
5.6.2 – AR – Evaluating Outcomes – Logic Model
Exercises & Additional Resources
Lab 5 – March 5th, 2026 @ 13:00 EST
