Course Description
Many fields of graduate study involve data whose meaning and trustworthiness are not obvious. Analytical techniques must be applied to bring out the implications of the data and to verify that apparent trends are not the result of chance. This course introduces such methods and is the basic course that serves as a prerequisite for further work in statistical methods. The primary emphasis is on techniques used in the behavioral sciences— education, psychology, sociology, human factors in industrial settings, and business.

This course will explore analysis and interpretation of research data; descriptive statistics; introduction to probability, sampling theory, statistical inference (binomial, normal distribution, t-distribution models); linear correlation, regression.

Course Objective
Upon completion of the course, students should be comfortable with basic descriptive statistics, inferential statistics, and the ability to reason logically using statistics. The focus will be less on formulaic computations and more on reasoning and interpreting statistical results.

Prerequisite Courses
None

Prerequisite Skills
Basic computer skills that are commonly required for online courses, such as typing.

Software and Technology

Textbooks

Required Online Textbook
Statistical Reasoning through Computation and R
by Brandon LeBeau and Andrew S. Zieffler
https://lebebr01.github.io/stat_thinking/

Optional/Supplemental Online Textbook
Introduction to Modern Statistics
by Mine Çetinkaya-Rundel and Johanna Hardin.
https://openintro-ims.netlify.app/