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Learning Goal

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Construct and interpret two-way frequency tables

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HSS.CP.A.4

**HSS.CP.A.4**: Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. For example, collect data from a random sample of students in your school on their favorite subject among math, science, and English. Estimate the probability that a randomly selected student from your school will favor science given that the student is in tenth grade. Do the same for other subjects and compare the results.

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HSS.CP.A.4: Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. For example, collect data from a random sample of students in your school on their favorite subject among math, science, and English. Estimate the probability that a randomly selected student from your school will favor science given that the student is in tenth grade. Do the same for other subjects and compare the results.

What you'll learn

  1. Construct a two-way frequency table from raw bivariate categorical data, including row totals, column totals, and the grand total
  2. Read joint and marginal frequencies from a two-way table and compute the corresponding probabilities for a randomly selected object
  3. Use the table as a sample space to approximate conditional probabilities, such as P(favors science | tenth grade), by restricting to a row or column
  4. Decide whether two categorical events are independent using table-based probabilities (comparing a conditional probability to a marginal, or a joint probability to the product of marginals)
  5. Interpret and compare conditional probabilities across categories in context, distinguishing association from causation

Slides

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1

Construct and probabilities

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2

Conditional and independence

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Practice

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