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https://github.com/paulnorthrop/smovie

Some movies to teach statistical concepts
https://github.com/paulnorthrop/smovie

central-limit-theorem correlation-coefficient extremal-types-theorem extremes hypothesis-testing likelihood-ratio-test linear-regression log-likelihood movie probability-distributions regression score-test statistical-concepts statistics statistics-learning teaching teaching-materials test-statistic wald-test

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Some movies to teach statistical concepts

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README

        

---
output: github_document
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```

# smovie

[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/paulnorthrop/smovie?branch=master&svg=true)](https://ci.appveyor.com/project/paulnorthrop/smovie)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/smovie)](https://cran.r-project.org/package=smovie)
[![Downloads (monthly)](https://cranlogs.r-pkg.org/badges/smovie?color=brightgreen)](https://cran.r-project.org/package=smovie)
[![Downloads (total)](https://cranlogs.r-pkg.org/badges/grand-total/smovie?color=brightgreen)](https://cran.r-project.org/package=smovie)

### Some Movies to Illustrate Concepts in Statistics

### What does smovie do?

The `smovie` package provides movies to help students to understand statistical
concepts. The [`rpanel` package](https://cran.r-project.org/package=rpanel) is
used to create interactive plots that move to illustrate key statistical ideas
and methods. The movies cover the topics of probability distributions; sampling distributions of the mean (central limit theorem), the median, the maximum (extremal types theorem) and the (Fisher transformation of the) correlation coefficient; simple linear regression; hypothesis testing.

### An example

The function `wws` produces a movie to visualise the Wald, Wilks and score likelihood-based test statistics, for a model with a scalar unknown parameter. The user can change the value of the parameter under a simple null hypothesis and observe the effect on the test statistics. The following code uses the log-likelihood from a binomial experiment and considers the null hypothesis that the success probability $\theta$ is equal to $\theta_0$. The user may specify their own log-likelihood.

```{r, eval = FALSE}
wws(theta0 = 0.5)
```

### Installation

To get the current released version from CRAN:

```{r installation, eval = FALSE}
install.packages("smovie")
```

### Vignettes

See `vignette("smovie-vignette", package = "smovie")` for an overview of the
package.