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4 OnTRACK Grade 7 Math: Number and Operations

Students will learn how to apply mathematical process standards to represent and use real numbers in a variety of forms.

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19 OnTRACK Grade 7 Math: Proportionality

Students will learn to use proportional relationships to describe dilations; to explain proportional and non-proportional relationships involving slope; and to use proportional and non-proportional relationships to develop foundational concepts of functions.

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7 OnTRACK Grade 7 Math: Expressions, Equations, and Relationships

Students will learn to develop mathematical relationships and make connections to geometric formulas; use geometry to solve problems; use one-variable equations or inequalities in problem situations; and use multiple representations to develop foundational concepts of simultaneous linear equations.

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4 OnTRACK Grade 8 Math: Number and Operations

Students will learn how to apply mathematical process standards to represent and use real numbers in a variety of forms.

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11 OnTRACK Grade 8 Math: Proportionality

Students learn to to use proportional relationships to describe dilation; explain proportional and non-proportional relationships involving slope; and use proportional and non-proportional relationships to develop foundational concepts of functions.

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9 OnTRACK Grade 8 Math: Expressions, Equations, and Relationships

Students will learn to develop mathematical relationships and make connections to geometric formulas; use geometry to solve problems; use one-variable equations or inequalities in problem situations; and use multiple representations to develop foundational concepts of simultaneous linear equations.

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5 OnTRACK Grade 8 Math: Two-Dimensional Shapes, Measurement, and Data

Students will learn to develop transformational geometry concepts and to use statistical procedures to describe data.

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7 Chapter 9: Hypothesis Testing

In this chapter, students will learn how to perform a hypothesis test and interpret its results.

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3 Chapter 1: Exploring Data

In this chapter, we introduce statistics, how it is used, and the types of data we come across in real life.

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4 Chapter 7: Sampling Distributions

In this chapter, students will describe and model variability using population and sampling distributions.

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7 Chapter 8: Confidence Intervals

In this chapter, students will learn how to construct and interpret a confidence interval for a population mean and a population proportion.

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5 Chapter 10: Comparing Two Groups

In this chapter, students interpret confidence intervals and the results of hypothesis tests for the difference between two means and the difference between two proportions.

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5 Chapter 3: Representing Categorical Data

In this chapter, we explore the different ways to display categorical data and draw conclusions based on the representations.

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8 Chapter 2: Data Collection, Sampling, and Experimental Design

In this chapter, we explore various methods of data collection and potential problems that may occur when collecting data.

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9 Chapter 6: Probability

In this chapter, students explore probability and random variables.

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6 Chapter 4: Representing Quantitative Data

In this chapter, we explore different ways to display quantitative data, and draw conclusions based on the representations.

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7 Chapter 11: Exploring Bivariate Data

In this chapter, students explore the relationship between two quantitative variables. Students will analyze scatterplots for strength, direction, and form; interpret the correlation coefficient; determine the line of best fit using least-squares regression; use the line of best fit to make predictions for a value of *y* given a value of *x*; interpret the slope and the *y*-intercept; learn about alternative methods of finding the line of best fit, including the median-median line and the absolute value line; and identify outliers and influential points and their effects on the regression line and correlation coefficient.

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6 Chapter 5: Measuring Center and Spread

In this chapter, students will learn multiple measures for center and spread, and will be introduced to the normal distribution and the empirical rule.

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2 Instructional Support Ancillaries for Statistics

Ancillaries for TEA Statistics