M111:ModelingwithData:One-VariableMeasurementData

 Modeling with Data: One-Variable Measurement Data

How much carbon dioxide is emitted daily in New York City? How many hours do your classmates spend on social media? Some important questions about the world don't have a single precise answer — they lead to a set of data. The tools and methods of statistics with one-variable measurement data can help us better understand our world, address the challenges of our time, and advocate for change.

In M111 Modeling with One-Variable Measurement Data, you will:


• Pose and analyze meaningful statistical questions that yield one-variable measurement data
• Use data displays and quantitative methods to draw conclusions, gain insight, and generate new questions
• Summarize data sets with measures of center and spread, and reason about what differences in those measures mean
• Model data with normal distributions and estimate population percentages, using technology to create and analyze histograms and other visual displays

Examples of careers that use M111 concepts: statistics, economics, biology, and computer science.

Associated Badges

Prerequisites for This Badge

Understanding of fractions, decimals, and percentages; comfort with using formulas

Learning Goals

Content & Practice Expectations

Each badge framework describes the mathematics skills and understandings that students will need to demonstrate to earn each badge through a set of Content & Practice Expectations (CPEs).

Assessments

Introduction to Badge Assessments

This document provides an overview of the different badging forms of assessment.

Pre-/Post-Task

These tasks should be administered before instruction begins on a new badge and again as badge instruction comes to a close. The pre-task gives students an opportunity to see where their learning is headed, identify any relevant background knowledge or skills they already possess, and establish a starting point for the badge. The post-task provides an opportunity for students to demonstrate what they have learned and compare their new thinking to their original responses. Together, these tasks help students recognize their growth over time while providing teachers with meaningful information to guide instruction and support learning.

Performance Assessments

Each task has a teacher guide, scoring guidance, and student versions (docx format) in English and Spanish.

Portfolio Resources

A portfolio of evidence consists of student-produced artifacts that demonstrate proficiency against a badge’s CPEs. The portfolio development process involves students selecting and reflecting on artifacts that showcase their understanding of badge CPEs, followed by iterative teacher review and student-teacher conferencing until the work demonstrates proficiency.

Modeling with Data: One-Variable Measurement Data | XQ Learning