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Bias

Bootstrap statistics

Bootstrap samples

Margin of error

Population

Alternative hypothesis

Standard error

Bootstrap distributions

Confidence level

Randomization distribution

Interval estimate

Statistically significant

P-value

Hypothesis test

Null hypothesis

Observed sample statistic

1. ____________________ are constructed by applying the key idea that if the sample is representative of the population, then the population can be approximated by many, many copies of the sample data.

1. We typically use the inferential technique of a _______________________ to investigate a claim about a population parameter.

1. When performing a hypothesis test, the ____________________ is typically one that indicates that there is no effect or no difference and is the default assumption.

1. A _____________________ is constructed by simulating many samples in a way that assumes the null hypothesis is true, uses the original sample data, and mirrors the way the data in the original sample were collected.

1. To construct a bootstrap distribution, we first generate __________________ by sampling with replacement from the original sample, using the same sample size.

1. Statistical inference enables us to use information in a sample to understand properties of a ________________.

1. The p-value is the proportion of the randomization distribution that is as extreme as, or more extreme than, the ____________________.

1. A _________________ is the probability of obtaining a sample statistic that is at least as extreme as the original sample statistic, under the assumption that the null hypothesis is true.

1. Since sample statistics vary from sample to sample, we need to get some sense of the accuracy of the statistic, for example, from the _________________.

1. One way to construct a 95% confidence interval is to obtain the standard deviation of a bootstrap distribution, also known as the ___________________, and use the fact that the margin of error will be twice this standard deviation.

1. If the p-value is less than the significance level, then we conclude that the observed sample results would be unlikely to occur just by random chance if the null hypothesis were true, and thus the observed sample results provide _____________________evidence against the null hypothesis and in support of the alternative hypothesis.

1. A range of plausible values for the population parameter is a(n) _____________________.

1. In one approach to constructing a confidence interval, the tails of the bootstrap distribution are chopped off and a specified percentage (determined by the ___________________ ) of the values in the middle are kept. These cutoffs (also known as the percentiles) form the confidence interval.

1. For statistical inference to be valid, the data must be collected in a way that does not introduce _____________.

1. When performing a hypothesis test, the ____________________ is the claim for which we seek evidence and is determined by the research question.

1. When constructing a bootstrap distribution, ____________________ are calculated for each of the bootstrap samples and plotted in dotplot.