Introduction
Students in high school use Tuva to investigate key concepts of statistics related to shape, center, and spread of distributions. Through the rich real-world contexts of Tuva datasets, students are able to examine key features of distributions in order to draw valid conclusions.
The dynamic nature of Tuva allows students to quickly compare distributions both visually and numerically using dot plots, box plots, and histograms. Additionally, high school students use Tuva to build models for bivariate data that are linear or nonlinear. The modeling features of Tuva allow students to either construct a function from scratch to fit a set of data or to compute a regression model of best fit. Students are then able to view summary statistic parameters for the model and use those to make predictions based on the context of the dataset they are working with in order to answer real-world problems.
Standard Deviation
Standard deviation is a challenging topic for students. Tuva can help students conceptually understand standard deviation through visual representation. Students use a reference lines to inspect the amount of overlap of two distributions in terms of the standard deviation, and use that relationship to draw conclusions. By seeing the standard deviation visually and immediately putting it into a real-world context, students have a much better understanding of this powerful statistical concept.
Creating Linear & Nonlinear Models
Students use Tuva to dynamically build functions to model data in context. Students can see the impact of changing the coefficient of a quadratic model as they attempt to fit their function to a dataset. Tuva's modeling features strengthen student's conceptual understanding of the parameters of a function, while also highlighting the purpose of building a mathematical model in order to make predictions about real-world scenario.