In this lecture, we further review the use of confidence intervals to summarize empirical results from simulation as we move from thinking about absolute performance estimation (i.e., using one model system to estimate one parameter) to relative performance estimation (i.e., comparing two model systems to make an inference about whether they differ). This allows us to discuss how confidence intervals are used in regression analysis and start to motivate how to build confidence intervals that are summarizes of 2-sample (instead of 1-sample) t-tests. We had to stop a little early, and so the next lecture will discuss how to convert paired t-tests and two different types of 2-sample t-tests into 2-sample confidence intervals (which are compared to 0).
Archived lectures from undergraduate course on stochastic simulation given at Arizona State University by Ted Pavlic
Tuesday, November 16, 2021
Lecture J4 (2021-11-16): Estimation of Relative Performance
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