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U.S. President -- Data Analysis & Statistics Inquiry - 21st Century Math Project

Rated 4.69 out of 5, based on 113 reviews
4.7 (113 ratings)
38,670 Downloads
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Clark Creative Math
17.4k Followers
Grade Levels
6th - 12th
Resource Type
Standards
Formats Included
  • Zip
  • Google Apps™
Pages
12 pages
Clark Creative Math
17.4k Followers
Includes Google Apps™
The Teacher-Author indicated this resource includes assets from Google Workspace (e.g. docs, slides, etc.).
Also included in
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Description

Engage students in data analysis through use of Presidential data in this 21st Century Math Project. Students will create box and whisker, stem and leaf, histograms and scatterplot through their investigations.

In the end, students will take on the inquiry question: "Do US Presidents with the most children live longer after they have been inaugurated?" ***THIS PRODUCT HAS BEEN UPDATED WITH A GOOGLE SLIDES INTERACTIVE VERSION INCLUDED. REDOWNLOAD IF YOU HAVE IT ALREADY***

-- In "He Entered a Young Man", students will make a parallel box-and-whisker plot by hand of the ages of the US Presidents at the time of their inauguration. They will use the box-and-whisker plot to answer the following questions.

-- In "Oval Office Analysis", students will use the data of the presidents to complete a variety of data displays including: stem and leaf plot, histograms, frequency distribution, mean, median, mode, range, box and whisker plots.

-- In "Presidential Inquiry", students will explore correlation of bivariate data to determine if a relationship exists between the number of children of a president has and their longevity after inauguration.

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Measures of Central Tendency & Data Analysis

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Total Pages
12 pages
Answer Key
Included
Teaching Duration
3 days
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Standards

to see state-specific standards (only available in the US).
Display numerical data in plots on a number line, including dot plots, histograms, and box plots.
Giving quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation), as well as describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered.
Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.

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