Data Analysis Tutorials

The Poisson distribution models the probability of a certain number of events occurring within a fixed interval. See how it's applied in real-world scenarios like queueing theory and traffic modeling.

Learn how the AUC-ROC curve assesses binary classification models, focusing on performance across thresholds, particularly in imbalanced datasets. Use Python’s libraries to compute AUC values and compare classifiers in one workflow.

A winsorized mean reduces the influence of outliers by capping extreme values at specific percentiles, preserving the overall structure of the dataset. Read further to learn how to calculate the winsorized mean using Python for hands-on practice.

Learn how to effectively use VBA in Excel to automate tasks, create macros, and enhance your data processing skills with practical examples and best practices.

Explore how using a SQL alias simplifies both column and table names. Learn why using a SQL alias is key for improving readability and managing complex joins.

Use the tabulate library in Python to create well-formatted tables. Learn about its advanced features and options for customizing table appearance.

Simplify your data models with Excel’s Goal Seek, one of its powerful What-If Analysis tools. Solve real-world problems like loan payments and revenue targets.

Create compelling pie charts in Tableau with clear step-by-step instructions for importing data, adjusting sizes, and customizing colors. Discover advanced methods like grouping categories and adding filters.

LEFT JOIN and LEFT OUTER JOIN in SQL are identical, with no functional difference between them. Keep reading to explore practical examples and discover how to apply these joins effectively in your queries.

Learn how to compare two columns in Excel for matches and for duplicates using methods like the equals operator, IF() function, EXACT(), VLOOKUP(), and more.

Learn how to extract and format text position or delimiter using Excel substring functions, including LEFT(), RIGHT(), MID(), and more, with step-by-step instructions.

Learn how to create a contingency table and perform chi-square tests in R using the chisq.test() function. Discover practical applications and interpret results with confidence.