Unit 1 - Measurement in Data Overview

This unit offers a sustained and focused examination of statistics and probability to support the development of students’ quantitative literacy. Statistics and probability help us perform essential real-world tasks such as making informed choices, deciding between different policies, and weighing competing knowledge claims. While topics of statistics and probability are commonplace in high school geometry courses, students often have limited opportunities to engage in statistical and probabilistic reasoning and sense-making. To move students toward a sophisticated understanding of data, students are expected to think about data sets as distributions which are functions that associate data values with their frequency or their probability. This encourages students to connect their knowledge of functions to concepts of statistics and probability, creating a more complete understanding of mathematics. Throughout the unit, students generate their own data through surveys, experiments, and simulations that investigate some aspect of the real world. They engage in statistical calculations and probabilistic reasoning as methods of analysis to make sense of data and draw inferences about populations. Incorporating statistics and probability in the same course as geometry allows students to experience two distinct forms of argumentation: geometrical reasoning as drawing conclusions with certainty about an ideal mathematical world, and probabilistic reasoning as drawing less-than-certain conclusions about the real world. The conclusions of a probability argument are presented as ranges that have varying degrees of certainty.

ENDURING UNDERSTANDINGS
Students will understand that ...

  • Statistics are numbers that summarize large data sets by reducing their complexity to a few key values that model their center and spread.
  • Distributions are functions whose displays are used to analyze data sets.
  • Probabilistic reasoning allows us to anticipate patterns in data.
  • The method by which data are collected influences what can be said about the population from which the data were drawn, and how certain those statements are.

KEY CONCEPTS

  • 1.1: The shape of data – Identifying measures of center and spread to summarize and characterize a data distribution
  • 1.2: Chance events – Exploring patterns in random events to anticipate the likelihood of outcomes
  • 1.3: Inferences from data – Using probability and statistics to make claims about a population