Lecture 3: Introduction to Programming and Measures of Central Tendency¶
This lecture introduces basic Python programming concepts alongside statistical measures of central tendency. Students will learn how to calculate and interpret mean, median, and mode, and understand when to use each measure.
Lecture 4: Graphing and Python Fundamentals¶
This session expands on Python programming by covering data types, variables, and lists for organizing data. Students will also learn to visualize quantitative data using dot plots and interpret the shape and distribution of datasets.
Lab 2: Computer Programming Introduction¶
Students use a Jupyter Notebook to explore data, interpret dot plots, and use variables and lists to perform calculations. This lab focuses on an understanding of data types, functions, and introductory data analysis.
Homework 1: Python Programming Practice¶
This assignment gives students the opportunity to practice foundational Python programming skills, requiring students to engage with variables, data types, arithmetic operators, and list manipulation.