Hereby Sentence (Updated!)

Is there evidence of racial bias in capital punishment?

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Hereby Sentence (Updated!)

Is there evidence of racial bias in capital punishment?

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Check it out! This lesson was just updated in September 2024, and we hope you love the new and improved version. If you've already prepped an earlier version, fear not, you can still find those here through Thursday December 5, 2024.

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2023-2024 Versions

In the fall of 2024, Citizen Math released updated versions of every lesson in our library, plus a few new ones! We know you may have already prepped an earlier version or planned a repeat of last year, so we're continuing to make these earlier versions available through Thursday December 5, 2024.

You can find the new lessons through the regular search, and we hope you love them as much as we do. You can read more about these updates in Our Community.

Is there evidence of racial bias in death penalty sentencing? Many U.S. states allow capital punishment for certain crimes. Some people argue that an “eye for an eye” is a fair punishment, while others believe the death penalty is unfairly imposed.

In this lesson, students analyze almost thirty years’ worth of data summarized in n-way frequency tables and discuss whether they see evidence of racial bias in who receives the death penalty and who doesn’t.

REAL WORLD TAKEAWAYS

  • Specific sets of data on the race of defendants receiving the death penalty can be interpreted to draw opposite conclusions regarding the prevalence of racial bias in sentencing.
  • Many people believe that in murder trials, defendants of some races are more likely to receive the death penalty than are defendants of other races.
  • According to data from North Carolina and Louisiana, the race of the victim has the greatest impact on how likely the defendant is to receive the death penalty. In North Carolina murder trials from 1980-2007, the defendant was 5x as likely to receive the death penalty when the victim was white than when the victim was Black. In Louisiana, the defendant was 1.6x as likely.

MATH OBJECTIVES

  • Interpret two-way frequency tables summarizing categorical data
  • Interpret relative frequencies - including joint and conditional frequencies – in the context of the data

Appropriate most times as students are developing conceptual understanding.
Algebra 1
One-Variable Statistics
Algebra 1
One-Variable Statistics
Content Standards S.ID.5 Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. S.ID.9 Distinguish between correlation and causation. S.IC.6 Evaluate reports based on data. S.MD.7 (+) Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).
Mathematical Practices MP.1 Make sense of problems and persevere in solving them. MP.2 Reason abstractly and quantitatively. MP.3 Construct viable arguments and critique the reasoning of others. MP.6 Attend to precision.

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