Students analyze contextual situations, focusing on single variable data and bivariate data, and are introduced to the concept of using data to make predictions and judgments about a situation.
In Unit 2, Statistics, students continue to analyze contextual situations, but in this unit, they focus on single variable data and then bivariate data. This is the first unit where students are introduced to the concept of using data to make predictions and judgments about a situation. Univariate data is described through shape, center, and spread by using mathematical calculations to support reasoning. Students begin to make judgments about whether data is consistent (analysis of spread) and whether mean or median is a better representation of a situation (center). Bivariate data is analyzed for whether the variables are related (correlation) and whether a linear model is the best function to fit a set of data (analysis of residuals), and students develop a linear model that can be used to predict future events. In Unit 2, students are introduced to the modeling cycle and complete a project on univariate data analysis and another on bivariate data analysis.
Unit 2 begins with analyzing and describing univariate data. Students expand on their knowledge of shape, center, and spread from 6th and 7th grade to further interpret and calculate measures of spread—learning about variance and standard deviation. Students capitalize on previous understandings of measures of center and different graphical representations to formalize their knowledge of which measures of center, shape, and spread are used in conjunction with one another, and how these help to inform the “big picture” of the data set they represent. A three-day project culminates study of this topic.
In Unit 2 students dive deeper into bivariate data—identifying categorical and numerical data, and choosing representations that match the data presented. Two-way tables are used to represent categorical data. Students calculate relative and conditional frequencies in two-way tables and expand on their understanding of the tool from 8th grade. Scatterplots are explored heavily in this unit, and students use what they know about association from 8th grade to connect to correlation in Algebra 1. Students base their understanding of regression on their previous learning about line of best fit. Also in this unit, students will learn to assess the validity of the model they have used (be it linear or another function) by using residuals. A three-day project culminates this topic, with a loose framework provided.
As Algebra 1 progresses, students will identify shapes of data sets according to the functions, and they will continue to bring in ideas about how to model data in line with functions. Students will explore S-ID.7 more heavily as they progress through the units of Algebra 1.
Pacing: 24 instructional days (22 lessons, 1 flex day, 1 assessment day)
This assessment accompanies Unit 2 and should be given on the suggested assessment day or after completing the unit.
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Internalization of Standards via the Unit Assessment:
Internalization of Trajectory of Unit:
Unit-Specific Intellectual Prep:
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descriptive statistics |
measures of center (mean, median) |
inferential statistics | spread (standard deviation, interquartile range) |
univariate data | shape (skew, symmetrical) |
bivariate data | normal distribution |
numerical data | outlier resistant |
categorical data | distribution |
sample | variance |
population | scatterplots |
statistical question | two-way frequency tables |
frequency graphs (histogram, bar graph, dot plot) | relative frequency |
box plot (box-and-whisker plot) | marginal frequency |
association | correlation (correlation coefficient) |
causation | residuals (residual plot) |
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Key: Major Cluster Supporting Cluster Additional Cluster
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