Question 1: parameter
Answer: numerical summary of a population or random process - categorical ~ proportion (π) - quantitative
~ mean (µ)
Question 2: statistic
Answer: numerical summary about a sample - categorical ~ proportion (p̂) - quantitative ~ mean (x̄)
Question 3: chance model
Answer: random process to investigate real-world phenomenon
Question 4: repetition of a simulation
Answer: set of flips equal to the sample size of the study
Question 5: statistical significance
Answer: unlikely to occur by random chance alone
Question 6: plausible
Answer: a term used to indicate that this chance model is a reasonable/believable explanation for the data
we observed
Question 7: 3S strategy for measuring strength of evidence
Answer: statistic, simulation, strength of evidence
Question 8: simulation
Answer: identify "by chance model" and repeatedly simulate values of the statistic that could've happened
when chance model is true
Question 9: strength of evidence
Answer: consider whether the value of the observed statistic is unlikely to occur if chance model is correct
Question 10: p-value
Answer: - standard way of indicating how far the observed value is in the tail - probability of obtaining the
observed statistic or more extreme values if the null hypothesis is true
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