Unit 8: Statistics and Bivariate Data

Patterns of association in bivariate data, including clustering, outliers, and various types of association (positive, negative, linear, and nonlinear).  

How to use straight lines to model relationships between two quantitative variables.  

The purpose of linear models in solving problems within the context of bivariate measurement data, specifically interpreting slope and intercept.  

How bivariate categorical data can be analyzed using frequencies and relative frequencies in two-way tables 1 .  

Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association.  

Informally fit a straight line to scatter plots with linear association and assess the model fit based on data point closeness.  

Identify the rate of change (slope) and initial value (intercept) by examining bivariate measurement data.  

Construct and interpret two-way tables to summarize data on two categorical variables and describe possible associations using relative frequencies.

Unit Assessment

SBA Type Questions