Statistical Thinking in Practice
The philosophy described above is reflected in the work students complete throughout the curriculum.
The following enrichment investigation from Chapter 6: Exploring Relationships Between Variables illustrates how students move beyond performing calculations to evaluating evidence, interpreting models, and making recommendations in authentic contexts.
Sample Enrichment: Student Absenteeism and Graduation Rates
You are part of a state education department evaluating whether student absenteeism is related to graduation rates across public high schools. Researchers collected data from several high schools to investigate whether average student absenteeism can be used to predict graduation rates.
The department has gathered the data shown in the table provided.
The department is reviewing a school where students average 14 absences per year and would like to estimate the expected graduation rate using a linear regression model.
Later, the school's actual graduation rate is reported to be 89%.
Before using this model to guide statewide attendance initiatives, the education department asks you to evaluate how well the model performed for this school and what the residual suggests about using absenteeism alone to predict graduation rates.
Sample Student Response
Students are expected not only to perform statistical calculations, but also to justify conclusions, communicate evidence, and make recommendations based on their analysis. The response below illustrates that progression.
