HSS-ID.B.6

Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.*

 
25 Lesson(s)
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Scatterplots and Non-Linear Data

Algebra I » Unit: Modeling With Statistics
Algebra I » Unit: Modeling With Statistics
James Bialasik
Amherst, NY
Environment: Suburban
 
Big Idea:

In this lesson students discover that some bivariate data should not be modeled by linear functions. Other functions are considered.

 
Favorites (7)
 
Resources (13)
scatterplots and non linear data image
   

Got Ups? A Statistics Unit Task

Algebra I » Unit: Modeling With Statistics
Algebra I » Unit: Modeling With Statistics
James Bialasik
Amherst, NY
Environment: Suburban
 
Big Idea:

Students are able to demonstrate all that they have learned throughout the statistics unit in this open-ended performance task.

 
Favorites (19)
 
Resources (15)
hollywood ups
   

Expore Correlation on Gapminder

12th Grade Math » Unit: Statistics: Bivariate Data
12th Grade Math » Unit: Statistics: Bivariate Data
James Dunseith
Worcester, MA
Environment: Urban
 
Big Idea:

Gapminder (http://www.gapminder.org/) is a powerful tool that packs a lot of data into one space.

 
Favorites (4)
 
Resources (20)
explore correlation image
   

Using a Scatterplot to Model Data

Algebra I » Unit: Modeling With Statistics
Algebra I » Unit: Modeling With Statistics
James Bialasik
Amherst, NY
Environment: Suburban
 
Big Idea:

Students collect and organize bivariate data and determine if a correlation between the variables exists.

 
Favorites (8)
 
Resources (14)
use a scatter plot image
   

Predicting the Height of a Criminal (Day 1 of 2)

Algebra I » Unit: Linear Functions
Algebra I » Unit: Linear Functions
Rhonda Leichliter
Rogers, AR
Environment: Rural
 
Big Idea:

The fun part of this lesson is to introduce to students that the femur length of a person is directly proportional to their height.

 
Favorites (3)
 
Resources (11)
femur to height
   

Predicting the Height of a Criminal (Day 2 of 2)

Algebra I » Unit: Linear Functions
Algebra I » Unit: Linear Functions
Rhonda Leichliter
Rogers, AR
Environment: Rural
 
Big Idea:

On Day 2 students complete the analysis and compare prediction equations calculated by hand and on the TI-Nspire calculator.

 
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Resources (11)
ti nspire
   

A Bivariate Relationship

Algebra I » Unit: Modeling With Statistics
Algebra I » Unit: Modeling With Statistics
James Bialasik
Amherst, NY
Environment: Suburban
 
Big Idea:

Students estimate a line of best fit and write a prediction equation modeling the data. Students then use a calculator to determine a line of best fit, before comparing the two equations.

 
Favorites (5)
 
Resources (10)
a bivariate relationship image
   

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

Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Jason Colombino
Salem, MA
Environment: Urban
 
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!

 
Favorites (7)
 
Resources (21)
 
Reflections (3)
cinderella slipper pic
   

Correlation and Causation

Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Jason Colombino
Salem, MA
Environment: Urban
 
Big Idea:

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

 
Favorites (8)
 
Resources (18)
 
Reflections (1)
family circus correlation resized
   

Our City Statistics Project and Assessment

Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Jason Colombino
Salem, MA
Environment: Urban
 
Big Idea:

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

 
Favorites (9)
 
Resources (17)
 
Reflections (1)
img 5153
   

Battery Life

Algebra I » Unit: Multiple Representations: Situations, Tables, Graphs, and Equations
Algebra I » Unit: Multiple Representations: Situations, Tables, Graphs, and Equations
Amanda Hathaway
Boston, MA
Environment: Urban
 
Big Idea:

Will the digital devices run out of charge on the way to school? Students reason and make predictions based on a graph and compare the charge of a cell phone and a video game player.

 
Favorites (2)
 
Resources (13)
 
Reflections (1)
battery life resized
   

Dabbling in Data

High School Physics » Unit: 1-D Kinematics
High School Physics » Unit: 1-D Kinematics
Sara Leins
Scottsdale, AZ
Environment: Suburban
 
Big Idea:

Starting the year off right with a data analysis activity to get students thinking on the first day of AP Physics 1!

 
Favorites (16)
 
Resources (16)
 
Reflections (2)
keep
   
Algebra I » Unit: Linear Functions
Rhonda Leichliter
Rogers, AR
Environment: Rural
 
Big Idea:

The emphasis in this lesson is to take students a little beyond the basics of Scatter Plots to explain the correlation coefficient (r) and the coefficient of determination (r squared).

 
Favorites (4)
 
Resources (11)
 
Reflections (1)
correlation
   

Predicting Water Park Attendance

Algebra I » Unit: Multiple Representations: Situations, Tables, Graphs, and Equations
Algebra I » Unit: Multiple Representations: Situations, Tables, Graphs, and Equations
Amanda Hathaway
Boston, MA
Environment: Urban
 
Big Idea:

From scatterplot to predictions. Students plot data, approximate a line of best fit, generate an equation for the line to make predictions.

 
Favorites (6)
 
Resources (11)
 
Reflections (1)
water park cropped lesson image
   

How does this fit? CalculatingCorrelation

Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Algebra I » Unit: Our City Statistics: Who We Are and Where We are Going
Jason Colombino
Salem, MA
Environment: Urban
 
Big Idea:

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

 
Favorites (2)
 
Resources (14)
 
Reflections (1)
img 5177

Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.

Informally assess the fit of a function by plotting and analyzing residuals.

Fit a linear function for a scatter plot that suggests a linear association.

Common Core Math
 
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