The NetMath program at the University of Illinois Urbana-Champaign provides college students and high school students an opportunity to enroll in college level courses to earn credits while learning about various mathematics and statistics topics. From completing calculus requirements, to applied linear algebra, an introduction to probability theory, or statistical analysis, NetMath has over 20 different course options to choose from. Recently, NetMath began offering Statistics 100, which is an introductory statistics course with particular emphasis on understanding statistical concepts and which tools are appropriate for which problems. This course, led by Senior Lecturer of Statistics, Ellen Fireman, is the second statistics course offered through the NetMath program. Fireman also provides instruction for the Statistics 200: Statistical Analysis course, which provides an accelerated introduction to the basic tools for quantitively oriented students.

“NetMath Stat 100 and Stat 200 share a basic philosophy,” Fireman recently said when asked about the NetMath Statistics courses. “We think everyone needs to understand basic statistics to navigate the modern world. Until recently common sense was sufficient for most people because daily life didn't involve processing a large amount of data. Now large stores of information have become readily available. You can either choose to ignore the information available or you can choose to make sense of it, which means learning statistics. Statistics is a collection of real tools — the key is to understand which one to use when and why.”

NetMath is the online self-paced distance learning program of the Department of Mathematics at the University of Illinois at Urbana-Champaign. The mission of NetMath is to bring academic resources from one of the nation's top public universities to students around the world. NetMath primarily provides mathematics courses to high school and college students around the world while also offering educational options for home-schooled students, working professionals, military personnel, and anyone interested in learning math.

Click here to learn more about courses offered through NetMath and how to enroll today!

Continue reading for more details about Stat 100 and Stat 200

Stat 100 focuses on the statistics that informed citizens need to understand to make basic decisions in medical matters, in politics, in finances, etc. Stat 200, which assumes more comfort with algebra, goes beyond that to start preparing students to be active practitioners of statistics in social sciences, natural sciences, business, etc. Students from all continents and of all ages, from high school students who’ve had algebra to professionals who wish to expand their horizons are welcome to apply to the NetMath courses.

Students tell us that after Stat 100 they...

• Read the newspaper in a new way, without their eyes glazing over when they see quantitative information.
• Know what questions to ask in evaluating studies and surveys.
• Understand what questions can and cannot be answered by statistical arguments.
• Feel more confident applying logical reasoning and common sense to quantitative topics but are very aware that their intuition can sometimes be shockingly wrong.

Students tell us that after Stat 200 they also...

• Know how to put together the many different calculation methods taught in other stats courses into a coherent, logical whole.
•  Are prepared to do real research requiring statistical methods.

Specific Course Contents

• Stat 100 includes experimental design (including basics of casual inference from observations), basic probability, descriptive statistics, linear regression, sampling and statistical inference, and hypothesis testing. Includes easy-to-use data analysis program.
• Stat 200 provides an accelerated introduction to the basic tools for quantitively oriented students, with particular emphasis on understanding which tools are appropriate for which problems. We cover experimental design (including basics of causal inference from observations), basic probability (both frequentist and Bayes), descriptive statistics, inference from samples (including null hypothesis significance tests), analysis of variance, multiple regression, logistic regression, and non-parametric methods. We include both an easy-to-use data analysis program. and exercises in the R programming language