In Auburngrads/teachingApps: Apps for Teaching Statistics, R Programming, and Shiny App Development

Confidence Intervals

Confidence intervals (CI) are useful tools for quantifying the uncertainty associated with a point estimate. The amount of uncertainty depends on a associated with du

• What does it mean to say "...the $100\times(1-\alpha)\%$ CI for $\theta =(\underline{\widehat{\theta}},\overline{\widehat{\theta}})$..."

• For $\alpha=0.05,$ a $95\%$ CI on $\theta$ this means

  • If an experiment were run $i$ times (each run producing a distinct data set)

  • The true (but unknown) value of $\theta$ would be in the interval $(\underline {\widehat {\theta_{i}}},\overline{\widehat{\theta_{i}}})$ in $95\%$ of those runs.

• A $95\%$ CI on $\theta$ does not mean $P(\underline{\widehat{\theta_{i}}} <\theta<\overline{\widehat{\theta_{i}}})=0.95$

  • For each experiment the probability $P(\underline{\widehat{\theta_{i}}} <\theta<\overline{\widehat{\theta_{i}}})$ is either $1$ or $0$

  • This is because $\theta$ is either in the interval, or it isn't

About this app

• The Examples tab

  • Walks through a 'not-so-real-world' example showing how ML Estimation works

• The Details Tab

  • Presents an interactive simulation showing how likelihood values are computed for different distributions

Auburngrads/teachingApps documentation built on June 17, 2020, 4:57 a.m.