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README.qmd
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---
title: ""
format:
gfm: default
number-sections: true
freeze: false
---
```{r, include = F}
registration_link <- "https://forms.gle/Lj9DfWFoySMRytUP8"
```
# January 2024 - A Week of R
The schedule listed below is for the next set of workshops. Workshops are typically offered just before the classes start in the Spring as well as the week after Spring finals. We anticipate that these classes will be offered in person, with no online option.
## Schedule
**Schedule is tentative and subject to change due to enrollment and lab availability**
- Location: Hardin 163 (North wing)
- Required materials: Laptop with [software installed](@sec-setup)
Register for the workshops [here](`r registration_link`).
We will send you an email about a week before the workshops are held with additional details.
{{< include schedule.qmd >}}
## Pricing
These workshops are developed and hosted by Statistics graduate students to assist UNL students, faculty, and staff with developing the R skills necessary for research and data analysis.
Individuals from outside the university are welcome to participate.
Proceeds from the workshops directly fund graduate student activities.
{{< include pricing.qmd >}}
We accept exact cash, checks, or a University cost object. We cannot accept N-cards.
::: {.content-visible unless-format="docx"}
::: {.callout-note collapse="true" }
### Corporate Group Rate
If you are anticipating registering more than 4 people who are **not UNL Affiliates** as a group, please feel free to contact [Susan Vanderplas](mailto:[email protected]?subject=R%20Workshops%20Pricing) for a group rate.
:::
::: {.callout-note collapse="true"}
### Independent Students (not part of a research lab)
If you are an independent student (e.g. not part of a research lab), and cannot afford the prices we've set, please contact [Susan Vanderplas](mailto:[email protected]?subject=R%20Workshops%20Pricing) about **1 week before the workshops are scheduled to see if scholarships are available.**
Include in your email how much you can afford to pay, why you need the workshops, and any other details you think are relevant.
Scholarships will depend on the number of registered participants.
We charge just enough to ensure that the instructors are paid for their time and effort, which is why scholarships depend on registration (which is not known until about a week before workshops start).
:::
Note that half-day workshops are those which are only offered from e.g. 9-12 or 1-4. We do not allow you to register and pay for only half of a full-day workshop.
:::
::: {.content-visible when-format="docx"}
See the [course website](https://unl-statistics.github.io/R-workshops/) for information about student scholarships, corporate group rates, and payment rules.
:::
## Sign Up
[Register here](`r registration_link`)
::: {.content-visible unless-format="docx"}
# Learning Outcomes
After the end of the this one week course, we expect you to be able to do the following:
::: {.callout-tip collapse="true"}
### Introduction to R
- Use R for scientific/statistical calculations
- Be able to create or read in data
- Be able to manipulate data using common patterns
- Explore data set characteristics and calculate summary statistics for real data sets
- Use the help functionality to find the functions you need to do what you want to do
- Install, use, and search for helpful external packages
:::
::: {.callout-tip collapse="true"}
### Graphics with `ggplot2`
- Visualize data using the ggplot2 package
- create basic plots
- understand the layer system
- be able to structure complex graphics
- Take a dataset and use static graphics to look for interesting features.
- Know about some aspects of human perception and what to avoid when plotting data.
:::
::: {.callout-tip collapse="true"}
### Data Wrangling
- Read data into R from different formats
- Investigate and work with different types of objects
- Use `dplyr` verbs such as summarize, group_by, mutate, filter, and select to modify and summarize data
- Use `tidyr` to convert data to wide and long formats, join related data sets, and clean messy data
:::
::: {.callout-tip collapse="true"}
### Statistical Modeling
- Fit linear and mixed models
- Create model summary output tables and plots
- Fit generalized additive models and generalized linear mixed models
:::
::: content-hidden
::: {.callout-tip collapse="true"}
### Dynamic Documents with <code>knitr</code> and <code>rmarkdown</code>
- Create documents that incorporate R code, R output, and text
- Write documents using markdown or LaTeX
- Use templates to structure markdown output into pdf, html, and docx formats
- Create slides using markdown and/or LaTeX with R output
:::
::: {.callout-tip collapse="true"}
### Web Scraping
- Understand the structure of HTML web pages (DOM, tags, attributes)
- Use CSS and XPATH to navigate HTML pages and select HTML nodes
- Extract data from HTML nodes
- Use APIs and other programmatic methods of accessing web-based data
:::
::: {.callout-tip collapse="true"}
### Shiny
- Design a user interface
- Create R code to respond to interactive elements of the UI
- Connect the user interface to reactive R code to create an interactive applet
:::
:::
:::
# Computer Setup {#sec-setup}
You will need to bring a laptop with the following software installed:
- [R](https://cloud.r-project.org/) (version 4.0.0 or greater)
- [RStudio](https://www.rstudio.com/products/rstudio/download/#download) (version 2021.09 or greater)
- Windows only:\
[Rtools](https://cloud.r-project.org/bin/windows/Rtools/)
- In R, please run the following code:
``` r
# this may take a LONG time...
install.packages(c("knitr", "rmarkdown", "tidyverse", "rvest", "xml2", "tinytex", "lme4", "emmeans"))
tinytex::install_tinytex()
```
You will need to make sure that you have sufficient permissions on your machine to install R packages from CRAN. If you do not have admin access to your own machine, please work with your administrator to ensure that you can install R packages during the workshop if necessary, as this is an important skill to learn.