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- HSS-ID.B.5Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.
- HSS-ID.B.6Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.*

- HSS-ID.B.6aFit 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.
- HSS-ID.B.6bInformally assess the fit of a function by plotting and analyzing residuals.
- HSS-ID.B.6cFit a linear function for a scatter plot that suggests a linear association.

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

Algebra I

Â» Unit:

Linear Functions

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.

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

Algebra I

Â» Unit:

Linear Functions

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

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

Algebra I

Â» 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!

Introduction to Scatter Plots, Line of Best Fit, and the Prediction Equation

Algebra I

Â» Unit:

Linear Functions

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).

Predicting Water Park Attendance

Algebra I

Â» Unit:

Multiple Representations: Situations, Tables, Graphs, and Equations

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

Leap of Faith!

Algebra I

Â» Unit:

Bridge to 10th Grade

Big Idea:Students will find a linear relationship between the number of rubber bands and height.

Box and Whisker Spiral Lesson

8th Grade Math

Â» Unit:

Statistical Spirals

Big Idea:Students can understand a box and whisker plot by constructing it.

Representing Bivariate Data Sets

Algebra II

Â» Unit:

Statistics: Two Variables

Big Idea:To create a graphical representation of a data set, we first consider whether the variables are categorical or quantitative. The type of display must be appropriate for the variable type!

How Much for a Used Car?

Algebra I

Â» Unit:

Data and Statistics

Big Idea:How can you determine a fair selling price for a used car? Students use scatterplots, lines of best fit, and correlation coefficients to predict an appropriate selling price.

Linear Regression and Residuals

Algebra II

Â» Unit:

Statistics: Two Variables

Big Idea:Examining the size and distribution of errors made by a model can help us determine if the model is appropriate.

Line of Best Fit Spiral Lesson

8th Grade Math

Â» Unit:

Statistical Spirals

Big Idea:We can use a line of best fit to understand trends in data

Describing Scatterplots

Algebra II

Â» Unit:

Statistics: Two Variables

Big Idea:The appearance of a scatter plot can tell us a lot about the relationship between the variables on the axes.

Performance Task: The Big Mac Index

12th Grade Math

Â» Unit:

Statistics: Bivariate Data

Big Idea:What insights can the price of a Big Mac offer about a country's economy?

Correlation Spiral Lesson

8th Grade Math

Â» Unit:

Statistical Spirals

Big Idea:The tighter packed the data, the better the correlation

Central Tendency Spiral Lesson

8th Grade Math

Â» Unit:

Statistical Spirals

Big Idea:We can use algebra to analyze central tendency questions

HSS-ID.B.6a

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.

HSS-ID.B.6b

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

HSS-ID.B.6c

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