—
title: “STA304 – Fall 2021”
author: “[ADD YOUR NAME HERE – STUDENT NUMBER]”
subtitle: Assignment 1
output:
pdf_document: default
—
“`{r, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
library(openintro)
“`
# Part 1
### Goal
### Procedure
### Showcasing the survey.
\newpage
# Part 2
## Data
“`{r, include = FALSE}
# Here you can load in (or simulate) and clean the data (you may need to do the cleaning in a separate R script – this is up to you).
# You may need additional chunks, in case you want to include some of the cleaning output.
“`
“`{r, include=FALSE}
# Use this to calculate some summary measures.
“`
“`{r, echo = TRUE}
# Use this to create some plots.
“`
All analysis for this report was programmed using `R version 4.0.2`.
## Methods
$$ include.your.mathematical.model.here.if.you.have.some.math.to.show $$
I will invoke a non-parametric bootstrap [2] to derive the 95\% confidence interval (CI) for the mean age of students in STA304.
## Results
“`{r, include = FALSE}
# Here you can run a your HT/CIs.
# Here you can derive the CIs of interest.
“`
## Bibliography
1. Grolemund, G. (2014, July 16) *Introduction to R Markdown*. RStudio. [https://rmarkdown.rstudio.com/articles_intro.html](https://rmarkdown.rstudio.com/articles_intro.html). (Last Accessed: May 5, 2021)
2. Dekking, F. M., et al. (2005) *A Modern Introduction to Probability and Statistics: Understanding why and how.* Springer Science & Business Media.
3. Allaire, J.J., et. el. *References: Introduction to R Markdown*. RStudio. [https://rmarkdown.rstudio.com/docs/](https://rmarkdown.rstudio.com/docs/). (Last Accessed: May 5, 2021)
\newpage
## Appendix
Here is a glimpse of the data set simulated/surveyed:
“`{r, echo = FALSE}
# glimpse(my_data)
“`