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 Algebra I Module 2: Descriptive Statistics In this module, students reconnect with and deepen their understanding of statistics and probability concepts first introduced in Grades 6, 7, and 8. ...

 Algebra I Module 5: A Synthesis of Modeling with Equations and Functions In Module 5, students synthesize what they have learned during the year about functions to select the correct function type in...

 Inferences and Conclusions from Data Students build a formal understanding of probability, considering complex events such as unions, intersections, and complements as well as the concept of...

 Module 2 builds on students’ previous work with units and with functions from Algebra I, and with trigonometric ratios and circles from high school Geometry. The heart of the module is the study of...

 Smooth curves are used to model given data distributions, eventually using the normal distribution to model data distributions that are bell shaped and symmetric. Tables and technology are used to...

 Student Outcomes Students describe data distributions in terms of shape, center and variability. Students use the mean and standard deviation to describe center and variability for a data...

 Student Outcomes Students draw a smooth curve that could be used as a model for a given data distribution. Students recognize when it is reasonable and when it is not reasonable to use a normal curve...

 Student Outcomes Students calculate z scores. Students use technology and tables to estimate the area under a normal curve. Students interpret probabilities in context.

 Student Outcomes Students use tables and technology to estimate the area under a normal curve. Students interpret probabilities in context. When appropriate, students select an appropriate normal...

 Student Outcomes Students model cyclical phenomena from biological and physical science using trigonometric functions. Students understand that some periodic behavior is too complicated to be modeled...

 Students will use trigonometric functions to model periodic phenomena (FTF.B.5) by fitting sinusoidal functions to data (SID.B.6a). Students use the properties of the graphs of sinusoidal...

 In Topic A, students observe and describe data distributions. They reconnect with their earlier study of distributions in Grade 6 by calculating measures of center and describing overall patterns or...

 In Topic B, students reconnect with methods for describing variability first seen in Grade 6. Topic B deepens students’ understanding of measures of variability by connecting a measure of the center...

 In Topic C, students reconnect with previous work in Grade 8 involving categorical data. Students use a twoway frequency table to organize data on two categorical variables. Students calculate the...

 In Topic D, students analyze relationships between two quantitative variables using scatterplots and by summarizing linear relationships using the least squares regression line. Models are proposed...

 Student Outcomes Students use linear, quadratic, and exponential functions to model data from tables, and choose the regression most appropriate to a given context. They use the correlation...

 Student Outcomes Students use a graphing calculator to construct the residual plot for a given data set. Students use a residual plot as an indication of whether the model used to describe the...

 Student Outcomes Students use technology to determine the value of the correlation coefficient for a given data set. Students interpret the value of the correlation coefficient as a measure of...

 Student Outcomes Students use data to develop a poster that involves the focus standards. Students construct a scatter plot of the data. Students analyze their data, examining the residual plot, and...

 Student Outcomes Students compare two or more distributions in terms of center, variability, and shape. Students interpret a measure of center as a typical value. Students interpret the IQR as a...

 Student Outcomes Students distinguish between categorical data and numerical data. Students summarize data on two categorical variables collected from a sample using a twoway frequency table.

 Student Outcomes Students summarize data on two categorical variables collected from a sample using a twoway frequency table. Given a twoway frequency table, students construct a relative frequency...

 Student Outcomes Students calculate and interpret conditional relative frequencies from twoway frequency tables. Students evaluate conditional relative frequencies as an indication of possible...

 Student Outcomes Students distinguish between scatter plots that display a relationship that can be reasonably modeled by a linear equation and those that should be modeled by a nonlinear equation.