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Module 2: Descriptive statistics

Topic A: Lesson 1: Dot plots and histograms

Learn
Representing data
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Frequency tables & dot plots
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Creating a histogram
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Interpreting a histogram
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Practice
Creating dot plotsGet 3 of 4 questions to level up!
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Reading dot plots & frequency tablesGet 3 of 4 questions to level up!
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Create histogramsGet 3 of 4 questions to level up!
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Read histogramsGet 3 of 4 questions to level up!
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Topic A: Lesson 1: Box plots and shape

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Worked example: Creating a box plot (odd number of data points)
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Worked example: Creating a box plot (even number of data points)
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Constructing a box plot
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Reading box plots
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Shapes of distributions
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Practice
Creating box plotsGet 3 of 4 questions to level up!
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Reading box plotsGet 3 of 4 questions to level up!
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Shape of distributionsGet 3 of 4 questions to level up!
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Quiz 1

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Topic A: Lesson 2: Describing the center of a distribution

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Statistics intro: Mean, median, & mode
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Mean, median, & mode example
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Calculating the mean
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Choosing the "best" measure of center
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Mean, median, and mode review
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Practice
Mean, median, and modeGet 5 of 7 questions to level up!
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Calculating the meanGet 3 of 4 questions to level up!
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Calculating the medianGet 3 of 4 questions to level up!
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Topic A: Lesson 3: Estimating centers and interpreting the mean as a balance point

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Comparing means of distributions
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Means and medians of different distributions
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Impact on median & mean: removing an outlier
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Impact on median & mean: increasing an outlier
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Missing value given the mean
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Mean as the balancing point
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Practice
Calculating the mean: data displaysGet 3 of 4 questions to level up!
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Calculating the median: data displaysGet 3 of 4 questions to level up!
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Effects of shifting, adding, & removing a data pointGet 3 of 4 questions to level up!
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Missing value given the meanGet 3 of 4 questions to level up!
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Quiz 2

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Topic B: Lesson 4: Summarizing deviations from the mean

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Example: Comparing distributions
(Opens a modal)
Mean absolute deviation example
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Practice
Comparing data distributionsGet 3 of 4 questions to level up!
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Comparing center and spreadGet 5 of 7 questions to level up!
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Mean absolute deviation (MAD)Get 3 of 4 questions to level up!
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Topic B: Lessons 5-6: Standard deviation and variability

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Population standard deviation
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Sample standard deviation and bias
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The idea of spread and standard deviation
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Population and sample standard deviation review
(Opens a modal)
Practice
Sample and population standard deviationGet 3 of 4 questions to level up!
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Quiz 3

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Topic B: Lesson 7: Measuring variability for skewed distributions (interquartile range)

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Interquartile range (IQR)
(Opens a modal)
Interpreting box plots
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Judging outliers in a dataset
(Opens a modal)
Practice
Interquartile range (IQR)Get 3 of 4 questions to level up!
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Interpreting quartilesGet 3 of 4 questions to level up!
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Identifying outliersGet 3 of 4 questions to level up!
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Topic B: Lesson 8: Comparing distributions

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Comparing distributions with dot plots (example problem)
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Comparing dot plots, histograms, and box plots
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Practice
Comparing distributionsGet 3 of 4 questions to level up!
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Comparing data displaysGet 3 of 4 questions to level up!
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Quiz 4

Level up on the above skills and collect up to 500 Mastery points

Topic C: Lessons 9-10: Bivariate categorical data

Learn
Two-way frequency tables and Venn diagrams
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Two-way frequency tables
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Two-way relative frequency tables
(Opens a modal)
Practice
Create two-way frequency tablesGet 3 of 4 questions to level up!
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Read two-way frequency tablesGet 3 of 4 questions to level up!
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Create two-way relative frequency tablesGet 3 of 4 questions to level up!
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Read two-way relative frequency tablesGet 3 of 4 questions to level up!
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Topic C: Lesson 11: Conditional relative frequencies and association

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Interpreting two-way tables
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Categorical data example
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Analyzing trends in categorical data
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Two-way relative frequency tables and associations
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Practice
Interpret two-way tablesGet 3 of 4 questions to level up!
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Trends in categorical dataGet 3 of 4 questions to level up!
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Quiz 5

Level up on the above skills and collect up to 600 Mastery points

Topic D: Lessons 12-13: Relationships between two numerical variables

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Constructing a scatter plot
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Example of direction in scatterplots
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Practice
Constructing scatter plotsGet 3 of 4 questions to level up!
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Positive and negative linear associations from scatter plotsGet 3 of 4 questions to level up!
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Topic D: Lesson 14: Modeling relationships with a line

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Fitting a line to data
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Estimating the line of best fit exercise
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Estimating with linear regression (linear models)
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Interpreting slope of regression line
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Interpreting y-intercept in regression model
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Practice
Eyeballing the line of best fitGet 3 of 4 questions to level up!
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Describing trends in scatter plotsGet 3 of 4 questions to level up!
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Estimating equations of lines of best fit, and using them to make predictionsGet 3 of 4 questions to level up!
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Interpreting slope and y-intercept for linear modelsGet 3 of 4 questions to level up!
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Quiz 6

Level up on the above skills and collect up to 600 Mastery points

Topic D: Lessons 15-18: Residuals

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Introduction to residuals and least squares regression
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Calculating residual example
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Introduction to residuals
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Residual plots
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Practice
Calculating and interpreting residualsGet 3 of 4 questions to level up!
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Residual plotsGet 3 of 4 questions to level up!
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Topic D: Lesson 19: Interpreting correlation

Learn
Bivariate relationship linearity, strength and direction
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Positive and negative associations in scatterplots
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Example: Correlation coefficient intuition
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Correlation and causality
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Calculating correlation coefficient r
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Correlation coefficient review
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Practice
Correlation coefficient intuitionGet 3 of 4 questions to level up!
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Quiz 7

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Unit test

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About this unit

"In this module, students reconnect with and deepen their understanding of statistics and probability concepts first introduced in Grades 6, 7, and 8. Students develop a set of tools for understanding and interpreting variability in data, and begin to make more informed decisions from data. They work with data distributions of various shapes, centers, and spreads. Students build on their experience with bivariate quantitative data from Grade 8. This module sets the stage for more extensive work with sampling and inference in later grades." Eureka Math/EngageNY (c) 2015 GreatMinds.org