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Study Edge Statistics

In Statistics, students build on the mathematics knowledge and skills from Kindergarten–grade 8 and Algebra I, broadening their knowledge of variability and statistical processes. Students will study sampling and experimentation, categorical and quantitative data, probability and random variables, inference, and bivariate data. Students will connect data and statistical processes to real-world situations and extend their knowledge of data analysis (TAC §111.47(b)(3)).

This video book is brought to you by TEA and Study Edge. It may be used to teach an entire Statistics course or to supplement traditional Statistics textbooks.

This open-education-resource instructional material by TEA is licensed under a Creative Commons Attribution 4.0 International Public License in accordance with Chapter 31 of the Texas Education Code.

Please provide feedback on Study Edge's open-education-resource instructional materials.

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2.07 Lurking and Confounding Variables

In this video, students learn the difference between lurking and confounding variables and how they affect results.

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2.08 Generalizability of Results and Conclusions

In this video, students learn how to interpret results and draw conclusions based on them.

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6.01 Probability and the Law of Large Numbers

In this video, students are introduced to the concept of probability using the Law of Large Numbers.

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6.02 Probability Terminology

In this video, students learn key terminology associated with probability.

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6.03 Venn Diagrams

In this video, students represent and calculate probabilities using Venn diagrams.

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6.04 Independent and Mutually Exclusive Events

In this video, students calculate probabilities for independent events and mutually exclusive events.

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6.05 Contingency Tables

In this video, students calculate probabilities using a two-way contingency table.

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6.06 Tree Diagrams

In this video, students calculate conditional probabilities using a tree diagram.

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6.07 Discrete Random Variables

In this video, students are introduced to discrete random variables.

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6.08 The Binomial Distribution

In this videos, students use the binomial distribution to find the expected value, variance, and probabilities associated with a binomial random variable.

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6.09 Binomial Approximation

In this videos, students approximate the binomial distribution with the normal distribution for large samples.

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Using Logical Reasoning to Prove Conjectures about Circles

Given conjectures about circles, the student will use deductive reasoning and counterexamples to prove or disprove the conjectures.

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Generalizing Geometric Properties of Ratios in Similar Figures

Students will investigate patterns to make conjectures about geometric relationships and apply the definition of similarity, in terms of a dilation, to identify similar figures and their proportional sides and congruent corresponding angles.

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Determining Area: Sectors of Circles

Students will use proportional reasoning to develop formulas to determine the area of sectors of circles. Students will then solve problems involving the area of sectors of circles.

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Making Conjectures About Circles and Segments

Given examples of circles and the lines that intersect them, the student will use explorations and concrete models to formulate and test conjectures about the properties and relationships among the resulting segments.

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Determining Area: Regular Polygons and Circles

The student will apply the formula for the area of regular polygons to solve problems.

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Making Conjectures About Circles and Angles

Given examples of circles and the lines that intersect them, the student will use explorations and concrete models to formulate and test conjectures about the properties of and relationships among the resulting angles.

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Solving Problems With Similar Figures

Given problem situations involving similar figures, the student will use ratios to solve the problems.

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5.01 Measuring Center of a Distribution

In this video. students will learn three measurements of center, calculate those measurements, and compare the mean and median of data sets.