STAT.MATH.6.I

Interpret the results of a hypothesis test using technology-generated results such as large sample tests for proportion, mean, difference between two proportions, and difference between two independent means.

Statistics · Texas Essential Knowledge and Skills (TEKS) · TEKS 2012

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Vocabulary
resultshypothesis testtechnology-generated resultslarge sample testsproportionmeandifference between two proportionsdifference between two independent means
Skills
  • interpret (results of a hypothesis test using technology-generated results) #dok2
  • identify (types of hypothesis tests: large sample tests for proportion, mean, difference between proportions, difference between independent means) #dok1
  • analyze (outputs from statistical software or calculators) #dok3
  • explain (the meaning of test results in context) #dok3
Learning Targets
  • I can identify different types of hypothesis tests, such as those for proportions and means. #dok1
  • I can interpret the results of a hypothesis test as provided by statistical software or calculators. #dok2
  • I can analyze and explain large sample test outputs for proportions, means, and differences between two groups. #dok3
  • I can explain what statistical test results mean within the context of a given situation. #dok3
Big Ideas
  • Statistical technology tools simplify and standardize hypothesis testing, but interpretation within context is essential.
  • Understanding and interpreting the output of various hypothesis tests is critical to drawing valid conclusions from data.
Essential Questions
  • How do you interpret the results of a hypothesis test generated by statistical technology?
  • What types of hypothesis tests can technology generate for proportions and means?
  • Why is it important to interpret hypothesis test results within the context of the data?
  • How can we use results from a hypothesis test to make decisions in real-world situations?
  • What are the limitations of relying solely on technology-generated hypothesis test outputs?