Bivariate Statistics - Complete Unit

Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
Bivariate Statistics - Complete Unit
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Product Description

This resource contains lessons covering the topics of scatterplots, lines of best fit, and two-way frequency tables from the 8th grade statistics and probability unit. In the Scatterplots lesson, students learn how to interpret bivariate data in a scatterplot, predict correlations, and analyze the linear equations of lines of best fit. In the Two Way Frequency Tables lesson, students learn to find missing values in two-way tables and calculate the relative frequencies for each category.

Includes an end-of-unit assessment (18 questions) AND project!

Each lesson includes:

+ SMART Notebook file (editable + PDF versions)

+ Guided Notes for students

+ Classwork Assignments

+ Exit Slips

+ Homework Assignments

+ Lesson Plans (including ideas for differentiation)

+ Answer Keys (for CW, Exit Slip & HW)

Project description:

This is a summative performance task or end-of-unit project on bivariate statistics. The process is step-by-step and walks students through the process of data collection and analysis. It’s a great way to get students engaged in hands-on research!

Students brainstorm a possible correlation to investigate between two quantitative variables. They write a research question, operationalize the variables, identify their target sample including an analysis of possible bias, and make predictions about the data.

Students then write the questions they will ask respondents and collect the data in a table. From the data, they calculate each measure of central tendency (mean, median, mode, & range) and use it to categorize the responses into 4 sub-groups. 

From there, students build a two-way frequency table and calculate the relative frequencies as a percentage. They then construct a scatterplot from the data set, for which they draw a line of best fit. Lastly, they write a linear equation from the line of best fit, interpret its slope and y-intercept in context of the variables, and use the equation to find additional points.

** Included is a list of possible quantitative variables to spark some ideas!

Total Pages
N/A
Answer Key
N/A
Teaching Duration
3 Weeks
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