Unit 8: Statistics and Probability

Bivariate Measurement Data Patterns: Scatter plots are utilized to display exact bivariate measurement data to investigate patterns, trends, and correlations between two quantitative variables.

Types of Associations: Data patterns can exhibit clustering, outliers, linear associations (positive or negative), or non-linear associations.

Linear Modeling Structures: Straight lines (lines of best fit or trend lines) are widely applied to model relationships between two quantitative variables, and the closeness of the data points helps informally assess how well the model fits the data.

Contextual Interpretations: In a linear model y=mx+b, the slope represents the constant rate of change and the y-intercept represents the initial value within the real-world context of the bivariate data.

Bivariate Data Structure: Patterns of association for categorical variables can be systematically displayed and analyzed using frequencies and relative frequencies within a two-way table.

Construct and Interpret Scatter Plots

Informally Fit Linear Models

Calculate and Predict with Equations

Interpret Slope and Intercepts

Construct and Analyze Two-Way Tables

Exit Tickets

Quiz

Assessment for the Unit