Learning Resource Type

Classroom Resource

Interactive Tools | Against All Odds: Inside Statistics

Subject Area

Mathematics

Grade(s)

9, 10, 11, 12

Overview

These interactive tools give students an opportunity to explore more about stemplots, control charts, and histograms as covered in the Against All Odds statistics series. Simulations allow students to explore statistics methods in-depth using their own data.

    Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

    MA19.GDA.9

    Represent the distribution of univariate quantitative data with plots on the real number line, choosing a format (dot plot, histogram, or box plot) most appropriate to the data set, and represent the distribution of bivariate quantitative data with a scatter plot. Extend from simple cases by hand to more complex cases involving large data sets using technology.

    Unpacked Content

    UP:MA19.GDA.9

    Vocabulary

    • Dot plots
    • Histograms
    • Box plots
    • Scatter plots
    • Univariate data
    • Bivariate data

    Knowledge

    Students know:
    • Techniques for constructing dot plots, histograms, scatter plots and box plots from a set of data.

    Skills

    Students are able to:
    • Choose from among data display (dot plots, histograms, box plots, scatter plots) to convey significant features of data.
    • Accurately construct dot plots, histograms, and box plots.
    • Accurately construct scatter plots using technology to organize and analyze the data.

    Understanding

    Students understand that:
    • Sets of data can be organized and displayed in a variety of ways each of which provides unique perspectives of the data set.
    • Data displays help in conceptualizing ideas and in solving problems.
    Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

    MA19.GDA.12

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

    Unpacked Content

    UP:MA19.GDA.12

    Vocabulary

    • Quantitative variables
    • Scatter plot
    • Residuals

    Knowledge

    Students know:
    • Techniques for creating a scatter plot,
    • Techniques for fitting linear functions to data.
    • Methods for using residuals to judge the closeness of the fit of the linear function to the original data.

    Skills

    Students are able to:
    • Accurately create a scatter plot of data.
    • Make reasonable assessments on the fit of the function to the data by examining residuals.
    • Accurately fit a function to data when there is evidence of a linear association.
    • Use technology to find the least-squares line of best fit for two quantitative variable.

    Understanding

    Students understand that:
    • Functions are used to create equations representative of ordered pairs of data.
    • Residuals may be examined to analyze how well a function fits the data.
    • When a linear association is suggested, a linear function can be fit to the scatter plot to aid in modeling the relationship.
    Link to Resource

    CR Resource Type

    Interactive/Game

    Resource Provider

    PBS
    Accessibility
    License

    License Type

    Custom
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