[7.SP.3-2.0] Assessing Data Overlap - Common Core Standard - Free Educational videos for Students in K-12 | Lumos Learning

## [7.SP.3-2.0] Assessing Data Overlap - Common Core Standard - Free Educational videos for Students in k-12

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#### DESCRIPTION:

Discover more Common Core Math at https://www.frontrowed.com Measure the difference between the centers of two numerical data distributions with similar variabilities by expressing it as a multiple of a measure of variability Front Row is a free, adaptive, Common Core aligned math program for teachers and students in kindergarten through eighth grade. Front Row allows students to practice math at their own pace - learning advanced concepts when they're ready and receiving remediation when they struggle. Front Row provides teachers with access to a detailed data dashboard and weekly email reports that show which standards are causing students difficulty, what small groups can be formed for interventions, and how their students are progressing in math. Discover more Common Core Math at https://www.frontrowed.com

#### OVERVIEW:

[7.SP.3-2.0] Assessing Data Overlap - Common Core Standard is a free educational video by Front Row.It helps students in grades 7 practice the following standards 7.SP.3,7.SP.B.3,.

This page not only allows students and teachers view [7.SP.3-2.0] Assessing Data Overlap - Common Core Standard but also find engaging Sample Questions, Apps, Pins, Worksheets, Books related to the following topics.

1. 7.SP.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..

2. 7.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..

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7.SP.3
7.SP.B.3

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