Learning objective
O2 Conduct a statistical hypothesis test for the proportion in the binomial distribution and interpret results in context; understand that a sample is used to make an inference about the population and that the significance level is the probability of incorrectly rejecting the null hypothesis.
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Statistics
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Binomial hypothesis test for a proportion
Aqa A Level MathematicsPaper 3
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O2 Conduct a statistical hypothesis test for the proportion in the binomial distribution and interpret results in context; understand that a sample is used to make an inference about the population and that the significance level is the probability of incorrectly rejecting the null hypothesis
- This point belongs to Statistics, especially Binomial hypothesis test for a proportion.
- You need to be able to o2 Conduct a statistical hypothesis test for the proportion in the binomial distribution and interpret results in context; understand that a sample is used to make an inference about the population and that the significance level is the probability of incorrectly rejecting the null hypothesis.
- The key ideas to know are significance level, binomial distribution, and proportion.
- Use the linked flashcards and practice questions to check recall, then practise applying the idea in an exam-style answer.
Key concepts
significance levelbinomial distributionproportionhypothesis test
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Open revision notesRelated learning objectives
- K1 Understand and use the terms population and sample; use samples to make informal inferences about the population; understand and use sampling techniques including simple random sampling and opportunity sampling; select or critique sampling techniques in context, including understanding that different samples can lead to different conclusions about the population.
Statistical sampling
- L1 Interpret diagrams for single-variable data, including understanding that area in a histogram represents frequency; connect to probability distributions.
Single-variable data diagrams
- L2 Interpret scatter diagrams and regression lines for bivariate data, including recognition of scatter diagrams with distinct sections of the population; understand informal interpretation of correlation; understand that correlation does not imply causation; calculations involving regression lines are excluded.
Scatter diagrams and regression lines
- L3 Interpret measures of central tendency and variation, extending to standard deviation; calculate standard deviation, including from summary statistics.
Central tendency and variation
- L4 Recognise and interpret possible outliers in data sets and statistical diagrams; select or critique data presentation techniques in context; clean data including dealing with missing data, errors and outliers.
Outliers and data presentation