Logistic regression is a modeling technique often used to predict a binary variable-a variable coded as 1 if an event of interest occurs (e.g., a borrower defaults on a loan) and coded as 0 otherwise. This note details how logistic regression applies the logistic function to generate a probability forecast for a binary event. It also includes an example of how to fit a logistic regression model to loan default data using StatTools (an Excel add-in). The StatTools output is then used to predict a loan's default as a function of the borrower's credit score.

Google Cloud Platform (GCP) offers a popular cloud computing resource for writing Structured Query Language (SQL) queries. The resource is called BigQuery. This note provides step-by-step information about accessing BigQuery and using it to upload and explore data. It also includes a quick-start guide.

Tableau is a powerful visualization software that supports the data analysis process. The program allows users to create custom visualizations from datasets of all sizes and types using a simple drag-and-drop interface. This note introduces new users to Tableau by providing guidance on connecting to data, exploring the interface, and creating a number of common visualizations.

Google Cloud Platform (GCP) offers Cloud Storage, a popular cloud computing resource for data storage. This note provides information about uploading data to Cloud Storage, creating BigQuery tables from data found in Cloud Storage, previewing files in Cloud Storage, and sharing Cloud Storage buckets.