Common Core Math Grade 8  Statistics & Probability: Standards
 Course type: Selfpaced
 Available Lessons: 10
 Average Lesson Length: 8 min

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chapter 1 / lesson 1What is Bivariate Data?  Definition & Examples
Course Summary
Easily create curriculum that meets Common Core math standards for grade 8 with this statistics and probability standards course. Our text and video lessons can be used in the classroom to help your students strengthen their understanding of the topics they need help with.To Start This Course Today
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2 chapters in Common Core Math Grade 8  Statistics & Probability: Standards
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About the Course
The Common Core State Standards were created in response to concerns that students in the United States were not progressing academically at the same rate as their international peers. By the end of 8th grade, per the standards, students should be able to formulate and reason expressions and equations, understand functions and how to use them to describe quantitative relationships and analyze two and threedimensional space and figures.
The lessons in this collection specifically target statistics and probability standards. By watching the fun video lessons in this chapter, students can access clear definitions and formulas, as well as examples and practice problems to better understand the following concepts:
 The meaning of bivariate data and process of creating and interpreting scatterplots
 How to define simple linear regression and use it to solve problems
 Analysis of maximums, minimums and outliers in a data set
 Ways to interpret the slope and intercept of a linear model
 Interpreting correlations in research results and linear relationships using data
 Categorical data and the twoway table
Our instructors present the lesson materials in an entertaining manner with fun visuals that can keep your students engaged as they work to grasp statistics and probability concepts. Video timelines are available that allow you to skip to main topics within any lessons if you need to revisit a concept your students don't fully understand. Each lesson also includes an assessment quiz you can have your students take to gauge their level of comprehension.
Collection Details
Patterns of Association (CCSS.MATH.CONTENT.8.SP.A.1)
Standard: 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.
The lessons for this standard help students understand the definition of bivariate data; how to create and interpret scatterplots; and finding maximums, minimums and outliers in a set of data.
Linear Association (CCSS.MATH.CONTENT.8.SP.A.2)
Standard: 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 lessons to help students review and grasp simple linear regression and problem solving using linear regression.
Interpreting Slope and Intercept (CCSS.MATH.CONTENT.8.SP.A.3)
Standard: 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.
In this lesson, students learn how to interpret the slope and intercept of a linear model.
Bivariate Categorical Data and TwoWay Tables (CCSS.MATH.CONTENT.8.SP.A.4)
Standard: Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a twoway table. Construct and interpret a twoway table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?
These lessons show students how to interpret correlations in research results, interpret linear relationships using data and understand the categorical data and twoway table.
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