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Bootstrapping a Confidence Interval for a Difference in Means Jennifer Thompson, MPH MS Meeting, October 18, 2007 1 Background This data is from a study of mechanically ventilated ICU patients which
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How to fill out bootstrapping a confidence interval
How to fill out bootstrapping a confidence interval:
01
Determine the sample size and collect the necessary data for your study.
02
Calculate the desired level of confidence, typically 95%, that you want for your interval.
03
Use bootstrapping techniques to generate a large number of resamples from your original data.
04
For each resample, calculate the desired statistic (e.g., mean, median, proportion).
05
Construct a histogram or distribution of the statistic values obtained from the resamples.
06
Calculate the lower and upper percentiles of the distribution to define the confidence interval.
07
Interpret the results in the context of your study, considering whether the interval contains meaningful values or not.
Who needs bootstrapping a confidence interval:
01
Researchers and scientists who want to estimate population parameters (e.g., mean, proportion) based on limited sample data.
02
Statisticians and data analysts who need to assess the uncertainty or variability associated with their estimates.
03
Decision-makers and policy-makers who rely on statistical inference to make informed decisions and recommendations.
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What is bootstrapping a confidence interval?
Bootstrapping a confidence interval is a statistical technique that involves resampling data with replacement to estimate the variability of a parameter estimate. It is used to calculate confidence intervals for a statistic when the underlying distribution is unknown or non-normal.
Who is required to file bootstrapping a confidence interval?
There is no specific requirement to file bootstrapping a confidence interval. It is a statistical technique used by researchers, statisticians, and data analysts to estimate the uncertainty around a parameter estimate.
How to fill out bootstrapping a confidence interval?
Bootstrapping a confidence interval is not filled out like a form. It is a statistical analysis technique that involves sampling and resampling data, estimating statistics, and calculating confidence intervals using resampled data.
What is the purpose of bootstrapping a confidence interval?
The purpose of bootstrapping a confidence interval is to obtain an estimate of the uncertainty or variability around a parameter estimate. It allows researchers to assess the precision and reliability of their results and make statistical inferences about the population from which the data were collected.
What information must be reported on bootstrapping a confidence interval?
The information reported on bootstrapping a confidence interval includes the parameter estimate, the confidence level chosen (e.g., 95%), the lower and upper bounds of the confidence interval, and any relevant assumptions or limitations of the analysis.
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