Measures of Central Tendency Guided Notes

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Stephanie Irick

52 Followers

Grade Levels

5th - 12th, Homeschool

Subjects

Math, Algebra, Statistics

Resource Type

Study Guides, Graphic Organizers, Scaffolded Notes

Standards

CCSS6.SP.B.5c

CCSS7.SP.A.2

CCSS7.SP.B.3

CCSS8.SP.A.3

CCSSHSS-ID.A.2

Formats Included

Word Document File

Pages

4 pages

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Stephanie Irick

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Description

These are guided notes for a lesson on measures of central tendency including mean, median, mode, and range.

There are several examples in the notes and the same data sets are used to show each measure of central tendency.

I have also included a teacher key to show you what to fill in the blanks as your students follow along.

To use these notes, I simply projected them onto my whiteboard, gave the students their blank copies, and had them follow along and write what I wrote. This works great when you don't have time, or students do not have the attention span, to take lengthy notes and still leave time for working independently! You could also save as a PDF and use an interactive board to annotate.

I have several others I am working on getting teacher keys for. Let me know if you're searching for a particular topic/lesson!

Total Pages

4 pages

Answer Key

Included

Teaching Duration

N/A

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Standards

to see state-specific standards (only available in the US).

CCSS6.SP.B.5c

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.

CCSS7.SP.A.2

Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be.

CCSS7.SP.B.3

Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable.

CCSS8.SP.A.3

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.

CCSSHSS-ID.A.2

Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.

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Stephanie Irick

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