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2 min read•october 28, 2020
Peter Cao
5-7% of the test
Roughly 2 to 3 multiple choice questions
After covering single-variable statistics, it’s time to increase the complexity a little bit with two variable statistics! We can deal with two variable statistics in two ways. With categorical variables, we can use two way tables to represent the relationship between two different categories of categorical variables. With quantitative variables, we can show the relationship between these using scatterplots. We will also see whether there is a relationship between two variables in both situations. This will link to later units as well. Our study of two-way tables will link to probability (Unit 4) and Chi-squared tests for homogeneity or independence (Unit 8). Our study of scatterplots will link to regression inference as well (Unit 9).
Three of the College Board's mathematical practices for AP Statistics are used in this unit, which will be outlined below.
Selecting Statistical Methods
This is useful when we decide whether we want to use two-variable statistics methods and the type to use or to use inference techniques learned later on.
Data Analysis
Using data analysis, we’ll figure out how to figure out different statistics from two-variable data sets and also find ways to model with them and draw conclusions.
Statistical Argumentation
In this unit, we will learn to argue about the strength of how much variables are related to each other, and also the most important sentence of this unit: correlation does not imply causation!
Categorical Variables
Two Way Tables
Joint Relative Frequencies
Marginal Relative Frequencies
Conditional Relative Frequencies
Side-by-side bar graphs
Segmented bar graphs
Mosaic plots
Correlation
Quantitative Variables
Scatterplots
Form
Direction
Strength
Unusual features (gaps, clusters, outliers)
Correlation Coefficient
Linear Regression (Least Squares Regression)
Extrapolation
Residuals
r, R^2. and s
Influential Points
Transforming Data Sets
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Practice your typing skills while reading Unit 2 Overview: Exploring Two-Variable Data
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