E. Predict It

Driving question
      How can one fact predict another?

      Learning objectives, requirement tasks, and mastery assessments
        • Distinguish different types of two variable scenarios and make an intuitive prediction of causality
          • Task: 
            • Participate in backchannel discussion about a TED Talk on statistics in the criminal justice system
            • Participate in second backchannel discussion about a TED Talk on statistical analysis of politics and racism
          • Mastery quiz: 
            • Understand the meaning of independence/dependence of variables
            • Understand the difference between correlation and causation and why variables that are correlated may have lurking variables that cause both
          • Mastery free-response topics:
            • Goal of one vs. two-variable stats
            • Correlation vs. causation
            • Application of correlation to the workplace

        • Use graphical methods to make a prediction on two variables' independence
          • Task
            • Analyze the difference in death rates of historical hurricanes based on [variable will be described in class].  Justify your results (individually) in writing in a Google Doc.
          • Mastery quiz: 
            • Using a bar graph or a two way table, identify when two categorical variables are dependent
            • Using stacked box plots or the means of different groups, identify when a categorical variable and a quantitative variable are dependent
            • Using a scatter plot, identify when two quantitative variables are dependent
        • In pairs, create a 2 minute video based on Gapminder.org or Tableau visualizations with two variables of your choice in order to explain patterns across nations.
          • Task:
            • Select a visualization tool and choose two variables with an interesting correlation.  Explain the variables, their relationship, potential causation, and interesting outliers.  Discuss changes over time.
          • Mastery free-response topics:
            • How to develop a compelling narrative that explains a data relationship
            • What your data proves about correlation and about causation
            • How to effectively display many variables simultaneously, examples from project
            • Use of multiple rounds of student and teacher feedback