Computational modeling is a powerful tool for teaching statistics – from simple descriptive statistics to conducting inference tests.
The sequence below will demonstrate a variety of statistical techniques by framing the use of those techniques into common questions asked in math and science classrooms. In addition to illustrating when specific tools should be used, the accompanying flipped lessons will demonstrate how to use the tools, how to integrate them into your curriculum, and pedagogical strategies to use with your students.
Single Variable Statistics – This section explores the statistical tools and approaches used in a single variable setting. For example, when displaying the distribution of data for experiments or observational studies with a single output like weight, pH, or temperature.
Two Variable Statistics – This section explores the statistical tools and approaches used in a two variable setting. For example, when displaying the relationship between inputs and outputs in experiments like the relationship between heights and weights.
Categorical Data – This section explores the statistical tools and approaches used in categorical settings. For example, when exploring the relationship between gender and education level.
Models and Inference – This section explains the statistical theories that were used to develop inference tools and how to use those tools in scientific settings. For example, testing the hypothesis, “Does Aspirin reduce the risk of Heart Attack?”, data can be analyzed statistically to arrive at a mathematically supported conclusion.