Download Terms: Sampling distribution, standard error of a statistic, Point

Terms:
Sampling distribution, standard error of a statistic, Point estimation, Interval estimation,
Estimator, Estimate, Unbiased estimator, Central Limit Theorem, Margin of error, Confidence
level, Hypothesis Testing, Null hypothesis, Alternative hypothesis, Decisions in hypothesis
testing, Type I error, Type II error, Level of significance, Test statistic formula, Rejection region,
Sample value of the test statistic, One-sided and two-sided alternative hypotheses, One-tailed and
Two-tailed rejection regions, p-value.
Notation:
Sample mean, Mean of the sample mean, Variance of the sample mean, Standard error of the
sample mean, Sample proportion, Mean of the sample proportion, Variance of the sample
proportion, Standard error of the sample proportion, Confidence level, Null hypothesis,
Alternative hypothesis, Probability of a type I error, Probability of a type II error, Level of
significance, p-value.
Lists:
2 measures of the quality of an interval estimator, 3 properties of the first confidence interval
formula (p. 113-4), 3 ways to decide which hypothesis is H0 and which is H1.
Other:
Connections between Probability and Statistics ideas (p. 86), The unbiased estimator for the
population mean, The unbiased estimator for the population proportion, Rule of thumb for the
use of the Central Limit Theorem, Difference between the Central Limit Theorem and the
theorem before the Central Limit Theorem, Difference between the two questions in middle of p.
110, Interpretation of a confidence interval estimate using the words of the problem, Rounding
rule of thumb for determining sample size, Interpretation of a confidence interval estimate using
the words of the problem, The assumption made in hypothesis testing, Writing a conclusion of a
hypothesis test using the words of the problem, How to make a decision based on a p-value,
Measuring the strength of evidence supporting H1.