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Unformatted text preview: ZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
Visualizing Hypothesis Testing Margin of Error A common Margin of Error (ME) is
ME=2 · SE VISUALIZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
Visualizing Hypothesis Testing 95% Conﬁdence Interval Sample Statistics ± 2 · SE VISUALIZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
Visualizing Hypothesis Testing Approximating the Population Key idea: if the observed sample is representative of the
population, then the population can be approximated by
many copies of the sample. VISUALIZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
Visualizing Hypothesis Testing Bootstrap Distribution Generate many samples (bootstrap samples) from the
original sample
Obtain the sample statistics (bootstrap statistics)
Create a distribution for the bootstrap statistics.
Assess the variability in sample statistics with a bootstrap
distribution.
Use a bootstrap distribution to calculate ME and
Conﬁdence interval VISUALIZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
Visualizing Hypothesis Testing Bootstrap Distribution To construct a bootstrap distribution we:
Generate bootstrap samples with replacement from the
original sample, using the same sample size
Compute the statistic of interest for each of the
bootstrap samples
Collect the statistics from many (usually at least 1000)
bootstrap samples into a bootstrap distribution VISUALIZING CONFIDENCE INTERVALS and HYPOTHE Checkpoint 2 and Checkpoint 3
Visualizing CONFIDENCE INTERVALS
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This note was uploaded on 03/12/2014 for the course STATS 10 taught by Professor Ioudina during the Spring '08 term at UCLA.
 Spring '08
 Ioudina

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