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Lessons for this topic haven’t been written yet. The objectives below show exactly what the syllabus expects, so you can plan with them in the meantime.
What Cambridge says you should be able to do, in our words. Codes are the topic number plus the objective’s position.
Understand the nature of a hypothesis test, the difference between one-tailed and two-tailed tests, and the terms null hypothesis, alternative hypothesis, significance level, rejection region (or critical region), acceptance region and test statistic.
Outcomes of hypothesis tests are expected to be interpreted in terms of the context in which the question is set.
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Formulate hypotheses and carry out a hypothesis test in the context of a single observation from a population that has a binomial or Poisson distribution, using direct evaluation of probabilities or, where appropriate, a normal approximation to the binomial or the Poisson distribution.
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Formulate hypotheses and carry out a hypothesis test concerning the population mean in cases where the population is normally distributed with known variance or where a large sample is used.
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Understand the terms Type I error and Type II error in relation to hypothesis tests.
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Calculate the probabilities of making Type I and Type II errors in specific situations involving tests based on a normal distribution or on direct evaluation of binomial or Poisson probabilities.
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