Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Empty Layer.

Home

Professional Learning

Instructional StrategiesLesson PlansProfessional Learning

BetterLesson helps teachers and leaders make growth towards professional goals.

See what we offerLearn more about

My Curriculum

Jason Colombino

Algebra I

Collins Middle

Salem, MA

Urban Environment

Similar Teachers

View all Master TeachersAlgebra I

(8 Units, 82 Lessons)

Unit 8 - Our City Statistics: Who We Are and Where We are Going(10 Lessons)

Unit 1 - Thinking Like a Mathematician: Modeling with Functions(10 Lessons)

Unit 2 - Its Not Always a Straight Answer: Linear Equations and Inequalities in 1 Variable (10 Lessons)

Unit 3 - Everything is Relative: Linear Functions(10 Lessons)

Unit 4 - Making Informed Decisions with Systems of Equations(12 Lessons)

Unit 5 - Exponential Functions(10 Lessons)

Unit 6 - Operations on Polynomials(7 Lessons)

Unit 7 - Interpret and Build Quadratic Functions and Equations(13 Lessons)

Unit 8 - Our City Statistics: Who We Are and Where We are Going(10 Lessons)

Our City Statistics Project and Assessment

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students demonstrate interpersonal and data literacy skills as use statistics to learn about their community.

17 Resources

16 Favorites

17 Resources

16 Favorites

Correlation and Causation

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will distinguish between correlation and causation by analyzing relevant real life examples!

18 Resources

15 Favorites

18 Resources

15 Favorites

Estimating Population Percentages - It is all normal

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will apply their knowledge of measures of center and spread to estimate population percentages in different contexts!

15 Resources

2 Favorites

15 Resources

2 Favorites

Summing it Up: Dot Plots, Histograms and Box Plots

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will learn different ways to represent and interpret data!

19 Resources

5 Favorites

19 Resources

5 Favorites

Making Relevant Comparisons: Comparing Populations

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will compare two or more data sets by using appropriate measures of center (median, mean) and spread (interquartile range, standard deviation).

15 Resources

4 Favorites

15 Resources

4 Favorites

What's the Frequency Kenneth? Summarizing Data with Frequency Tables

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will answer REM’s question by creating and interpreting frequency tables as another tool to organize and understand data!

19 Resources

4 Favorites

19 Resources

4 Favorites

Cinderella's Slipper: Scatterplots, Residuals and Goodness of Fit

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students explore the idea of Goodness of Fit for different data sets and learn to fit data that can be modeled with linear associations!

21 Resources

8 Favorites

21 Resources

8 Favorites

How does this fit? CalculatingCorrelation

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will using statistics to understand the goodness of fit for a linear model of bivariate data.

14 Resources

2 Favorites

14 Resources

2 Favorites

What does it mean? Interpreting linear models

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students will apply their understanding of slope and intercepts to model different contexts with linear functions!

18 Resources

2 Favorites

18 Resources

2 Favorites

Outliers and Outsiders: The Impact on Data

Algebra I

» Unit:

Our City Statistics: Who We Are and Where We are Going

Big Idea:Students real world relationships to gain understanding of the power of individual data points.

14 Resources

1 Favorite

14 Resources

1 Favorite