Algebra I - End of Course Topic, Family Guide
Algebra I - End of Course Topic, Family Guide - Spanish
Algebra I - Module 1, Topic 3, Family Guide
Algebra I - Module 1, Topic 3, Family Guide - Spanish
Algebra I - Module 2, Topic 2, Family Guide - Spanish
Algebra I - Module 2, Topic 2 Family Guide
Algebra I - Module 4, Topic 1 Family Guide
Algebra I - Module 4, Topic 1, Family Guide - Spanish
Algebra I - Module 4 Family and Caregiver Guide - Spanish
Algebra I - Module 4, Family and Caregiver Guide
Algebra I - Module 4, Topic 2, Family Guide - Spanish
Algebra I - Module 4, Topic 2 Family Guide
SLP Algebra I - Topic 1 Family Guide
SLP Algebra I - Topic 3 Family Guide
Algebra I - Module 1, Family and Caregiver Guide - Spanish
Family & Caregiver Guide
Algebra I - Module 1, Family and Caregiver Guide
Family & Caregiver Guide
Algebra I - Module 1, Topic 2: Sequences
In this topic, students explore sequences represented as lists of numbers, in tables of values, by equations, and as graphs on the coordinate plane. Students move from an intuitive understanding of patterns to a more formal approach of representing sequences as functions. In the final lesson of the topic, students are introduced to the modeling process. Defined in four steps—Notice and Wonder, Organize and Mathematize, Predict and Analyze, and Test and Interpret—the modeling process gives students a structure for approaching real-world mathematical problems.
Algebra I - Module 1, Topic 3: Linear Regressions
In this topic, students focus on the patterns that are evident in certain data sets and use linear functions to model those patterns. Using the informal knowledge of lines of best fit that was built in previous grades, students advance their statistical methods to make predictions about real-world phenomena. They differentiate between correlation and causation, recognizing that a correlation between two quantities does not necessarily mean that there is also a causal relationship. At the end of this topic, students will synthesize what they have learned to decide whether a linear model is appropriate.