Lab 1: Welcome to Biological Data Science

BI 255 · Bethune-Cookman University · Fall 2026

Author

Dr. Rosie Stanbrook-Buyer

Published

August 17, 2026

Welcome to BI 255!

Imagine you’re the data analyst for the Kansas City Chiefs. Your job: figure out which players are performing best, which games show unusual patterns, and how weather affects scoring. Every one of those questions is answered with data — and the tool most scientists and analysts use to do it is called R.

This course teaches you R. Not because it’s easy (though it gets easier fast), but because it is the most powerful free tool available for analyzing biological and scientific data.

By the end of this semester you will be able to:

Write real code that cleans, analyzes, and visualizes data
Apply statistical tests used in biology research
Build maps and interactive apps
Present your findings like a professional scientist

Part 1: What is R, and Why Should You Care?

R is a programming language designed specifically for data analysis and statistics. It is:

Free and open source — anyone in the world can use it
Powerful — used by biologists, doctors, data scientists, and sports analysts
In demand — knowing R is a job skill listed in thousands of positions

Fun Fact

R is used by the NFL, NBA, CDC, NASA, and almost every major research university. The same tool you learn in this class is used by professional analysts every day.

Posit Cloud is the website where you will write and run R code. Think of it as a Google Doc, but for code. You don’t need to install anything.

Part 2: Setting Up Posit Cloud

Follow these steps to get started:

Go to posit.cloud
Click Sign Up and create a free account (use your B-CU email)
Once logged in, click New Project → New RStudio Project
You should see a screen with three panels — this is your workspace

The RStudio Layout

Panel	Location	What it does
Console	Bottom left	Where R runs your code immediately
Source / Editor	Top left	Where you write and save scripts
Environment	Top right	Shows variables you’ve created
Files / Plots	Bottom right	Shows your files and any graphs

You’ll use all four panels in this course!

Part 3: Your First R Commands

Click in the Console (bottom left panel) and type exactly what you see below after the > symbol, then press Enter.

R as a Calculator

# Adding two numbers
2 + 2

[1] 4

# More math operations
10 - 3

[1] 7

4 * 6

[1] 24

20 / 4

[1] 5

2^3   # 2 to the power of 3

[1] 8

What is a # symbol?

The # symbol creates a comment — R ignores everything after it on that line. Comments are notes you write to yourself (or your professor!) to explain what your code does. Always comment your code.

NFL Scoring Example

Let’s use some real data. The Kansas City Chiefs scored these points across four games last season:

# Points scored by the Kansas City Chiefs
27 + 20 + 34 + 17

[1] 98

# What was their average score?
(27 + 20 + 34 + 17) / 4

[1] 24.5

Try It Yourself

What if they scored 31 in a fifth game? Change the code above to include that score and recalculate the average. Click in the console and try it!

Part 4: What is Quarto?

The document you are reading right now was made in Quarto. Quarto is a system that lets you combine:

Written text (like a lab report)
R code
The output and plots that code produces

…all in one beautiful document that you can export as a webpage, PDF, or Word file.

All your work this Semester will be Quarto documents

When you submit your work, you will render your Quarto file and submit the HTML output. This means your code, your explanations, and your results are all in one place.

Anatomy of a Quarto Document

A Quarto file (.qmd) has three parts:

1. The YAML Header — controls the document’s appearance (the stuff between the --- dashes at the very top)

2. Text sections — written in Markdown (plain text with simple formatting symbols)

3. Code chunks — blocks of R code surrounded by triple backticks (this is backtick `)

Here is what a code chunk looks like:

```{{r}}
# Your R code goes here
2 + 2
```

The output appears directly below it when you Render the document.

Keyboard Shortcut

To insert a new code chunk in Quarto, press Ctrl + Alt + I (Windows) or Cmd + Option + I (Mac).

To run code inside a chunk, press Ctrl + Enter (Windows) or Cmd + Enter (Mac).

Part 5: Create Your First Quarto Document

Let’s build one together.

In Posit Cloud, click File → New File → Quarto Document
Give it a title: "My First BI 255 Lab"
Choose HTML as the output format
Click Create

You’ll see a template document. Delete everything below the YAML header (the --- section at the top) and replace it with this:

## About Me

My name is [YOUR NAME] and I am taking BI 255.

I am interested in biology because...

## My First Calculation

Here is my first R code:

Then add a code chunk below it with this information:

# My favorite NFL team's last 3 scores
score_1 <- 24
score_2 <- 31
score_3 <- 17

# Calculate the average
average_score <- (score_1 + score_2 + score_3) / 3
average_score

[1] 24

What is <-?

The <- symbol is called the assignment operator. It stores a value into a named variable. Think of it like putting something into a labeled box:

score_1 <- 24 means “create a box called score_1 and put the number 24 inside it.”

You can then use score_1 anywhere in your code and R will remember it equals 24.

Click the Render button (blue arrow at the top) to generate your HTML document
It should open in a new tab — you just made your first data science document!

Part 6: Saving and Organizing Your Work

Always Save Your Work!

Posit Cloud saves automatically, but get in the habit of pressing Ctrl+S (or Cmd+S) frequently. Name your files clearly — for example, Lab1_LabTopic.qmd.

Good file naming habits:

Lab1_Introclass.qmd
BI255_Lab1_Sept17.qmd
untitled.qmd (avoid)
final_FINAL_v3.qmd (avoid)

3-Minute Knowledge Check

Close your notes. Answer these on your own — you have 3 minutes. We’ll go through the answers together after.

Knowledge Check Questions

1. What symbol do you use in R to assign a value to a variable?

a) => b) <- c) == d) ->

2. In R, what does the # symbol do?

a) Multiplies two numbers b) Marks the start of a comment c) Creates a new variable d) Closes a code chunk

3. True or False: You need to pay for software to use R and Posit Cloud in this course.

4. What file extension do Quarto documents use?

a) .r b) .html c) .qmd d) .doc

5. You type (27 + 31 + 14) / 3 in the R console and press Enter. What does R calculate?

Answers (Only reveal if you have answered the above questions)

1. b) <- — The assignment operator. You can also use = but <- is the convention in R.

2. b) Marks the start of a comment — R ignores everything after # on that line.

3. False — R is free and open source. Posit Cloud has a free tier that is sufficient for this course.

4. c) .qmd — Quarto Markdown files use the .qmd extension.

5. 24 — This is the average of three NFL game scores: (27 + 31 + 14) ÷ 3 = 72 ÷ 3 = 24.

Lab 1 Checklist

Before you leave today, make sure you have:

Created a Posit Cloud account
Run your first arithmetic commands in the Console
Created a new Quarto document
Added text and a code chunk to your document
Successfully rendered the document to HTML
Saved your file with a clear name

Bonus Challenge

Look up the current season scoring stats for your favorite NFL or NBA team. Add a new code chunk to your Quarto document that stores three of their recent game scores and calculates the average. Render it and show your instructor!

Before Next Class

Make sure you can log in to Posit Cloud from home
Read Chapter 2 of Intro2r (link on Canvas)

Where to Find the Textbook

All textbooks for this course are free online. Go to Canvas → Syllabus → Course Materials to find the links. You never need to buy a textbook for this class.

--- title: "Lab 1: Welcome to Biological Data Science" subtitle: "BI 255 · Bethune-Cookman University · Fall 2026" author: "Dr. Rosie Stanbrook-Buyer" date: "August 17, 2026" format: html: theme: cosmo toc: true toc-location: left toc-title: "In This Lab" toc-depth: 3 number-sections: false code-fold: false code-tools: true highlight-style: github smooth-scroll: true embed-resources: true callout-appearance: default execute: warning: false message: false echo: true --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ------------------------------------------------------------------------ ## Welcome to BI 255! Imagine you're the data analyst for the **Kansas City Chiefs**. Your job: figure out which players are performing best, which games show unusual patterns, and how weather affects scoring. Every one of those questions is answered with data — and the tool most scientists and analysts use to do it is called **R**. This course teaches you R. Not because it's easy (though it gets easier fast), but because it is the most powerful free tool available for analyzing biological and scientific data. By the end of this semester you will be able to: - Write real code that cleans, analyzes, and visualizes data - Apply statistical tests used in biology research - Build maps and interactive apps - Present your findings like a professional scientist ------------------------------------------------------------------------ ## Part 1: What is R, and Why Should You Care? **R** is a programming language designed specifically for data analysis and statistics. It is: - **Free and open source** — anyone in the world can use it - **Powerful** — used by biologists, doctors, data scientists, and sports analysts - **In demand** — knowing R is a job skill listed in thousands of positions ::: callout-note ## Fun Fact R is used by the NFL, NBA, CDC, NASA, and almost every major research university. The same tool you learn in this class is used by professional analysts every day. ::: **Posit Cloud** is the website where you will write and run R code. Think of it as a Google Doc, but for code. You don't need to install anything. ------------------------------------------------------------------------ ## Part 2: Setting Up Posit Cloud Follow these steps to get started: 1. Go to [**posit.cloud**](https://posit.cloud) 2. Click **Sign Up** and create a [free]{.underline} account (use your B-CU email) 3. Once logged in, click **New Project → New RStudio Project** 4. You should see a screen with three panels — this is your workspace ::: callout-tip ## The RStudio Layout | Panel | Location | What it does | |---------------------|--------------|------------------------------------| | **Console** | Bottom left | Where R runs your code immediately | | **Source / Editor** | Top left | Where you write and save scripts | | **Environment** | Top right | Shows variables you've created | | **Files / Plots** | Bottom right | Shows your files and any graphs | You'll use all four panels in this course! ::: ------------------------------------------------------------------------ ## Part 3: Your First R Commands Click in the **Console** (bottom left panel) and type exactly what you see below after the `>` symbol, then press **Enter**. ### R as a Calculator ```{r} # Adding two numbers 2 + 2 ``` ```{r} # More math operations 10 - 3 4 * 6 20 / 4 2^3 # 2 to the power of 3 ``` ::: callout-note ## What is a `#` symbol? The `#` symbol creates a **comment** — R ignores everything after it on that line. Comments are notes you write to yourself (or your professor!) to explain what your code does. Always comment your code. ::: ### NFL Scoring Example Let's use some real data. The Kansas City Chiefs scored these points across four games last season: ```{r} # Points scored by the Kansas City Chiefs 27 + 20 + 34 + 17 ``` ```{r} # What was their average score? (27 + 20 + 34 + 17) / 4 ``` ::: callout-tip ## Try It Yourself What if they scored 31 in a fifth game? Change the code above to include that score and recalculate the average. Click in the console and try it! ::: ------------------------------------------------------------------------ ## Part 4: What is Quarto? The document you are reading right now was made in **Quarto**. Quarto is a system that lets you combine: - Written text (like a lab report) - R code - The output and plots that code produces ...all in one beautiful document that you can export as a webpage, PDF, or Word file. ::: callout-important ## All your work this Semester will be Quarto documents When you submit your work, you will render your Quarto file and submit the HTML output. This means your code, your explanations, and your results are all in one place. ::: ### Anatomy of a Quarto Document A Quarto file (`.qmd`) has three parts: **1. The YAML Header** — controls the document's appearance (the stuff between the `---` dashes at the very top) **2. Text sections** — written in Markdown (plain text with simple formatting symbols) **3. Code chunks** — blocks of R code surrounded by triple backticks (this is backtick \`) Here is what a code chunk looks like: ```{{r}} # Your R code goes here 2 + 2 ``` The output appears directly below it when you **Render** the document. ::: callout-tip ## Keyboard Shortcut To insert a new code chunk in Quarto, press **Ctrl + Alt + I** (Windows) or **Cmd + Option + I** (Mac). To run code inside a chunk, press **Ctrl + Enter** (Windows) or **Cmd + Enter** (Mac). ::: ------------------------------------------------------------------------ ## Part 5: Create Your First Quarto Document Let's build one together. 1. In Posit Cloud, click **File → New File → Quarto Document** 2. Give it a title: `"My First BI 255 Lab"` 3. Choose **HTML** as the output format 4. Click **Create** You'll see a template document. **Delete everything below the YAML header** (the `---` section at the top) and replace it with this: ``` markdown ## About Me My name is [YOUR NAME] and I am taking BI 255. I am interested in biology because... ## My First Calculation Here is my first R code: ``` Then add a code chunk below it with this information: ```{r} # My favorite NFL team's last 3 scores score_1 <- 24 score_2 <- 31 score_3 <- 17 # Calculate the average average_score <- (score_1 + score_2 + score_3) / 3 average_score ``` ::: callout-note ## What is `<-`? The `<-` symbol is called the **assignment operator**. It stores a value into a named variable. Think of it like putting something into a labeled box: `score_1 <- 24` means "create a box called `score_1` and put the number 24 inside it." You can then use `score_1` anywhere in your code and R will remember it equals 24. ::: 5. Click the **Render** button (blue arrow at the top) to generate your HTML document 6. It should open in a new tab — you just made your first data science document! ------------------------------------------------------------------------ ## Part 6: Saving and Organizing Your Work ::: callout-important ## Always Save Your Work! Posit Cloud saves automatically, but get in the habit of pressing **Ctrl+S** (or **Cmd+S**) frequently. Name your files clearly — for example, `Lab1_LabTopic.qmd`. ::: Good file naming habits: - `Lab1_Introclass.qmd` - `BI255_Lab1_Sept17.qmd` - `untitled.qmd` (avoid) - `final_FINAL_v3.qmd` (avoid) ------------------------------------------------------------------------ ## 3-Minute Knowledge Check *Close your notes. Answer these on your own — you have 3 minutes. We'll go through the answers together after.* ::: callout-caution ## Knowledge Check Questions **1.** What symbol do you use in R to assign a value to a variable? a) `=>` b) `<-` c) `==` d) `->` **2.** In R, what does the `#` symbol do? a) Multiplies two numbers b) Marks the start of a comment c) Creates a new variable d) Closes a code chunk **3.** True or False: You need to pay for software to use R and Posit Cloud in this course. **4.** What file extension do Quarto documents use? a) `.r` b) `.html` c) `.qmd` d) `.doc` **5.** You type `(27 + 31 + 14) / 3` in the R console and press Enter. What does R calculate? ::: ::: {.callout-caution collapse="true"} ## Answers (Only reveal if you have answered the above questions) **1.** b) `<-` — The assignment operator. You can also use `=` but `<-` is the convention in R. **2.** b) Marks the start of a comment — R ignores everything after `#` on that line. **3.** **False** — R is free and open source. Posit Cloud has a free tier that is sufficient for this course. **4.** c) `.qmd` — Quarto Markdown files use the `.qmd` extension. **5.** `24` — This is the average of three NFL game scores: (27 + 31 + 14) ÷ 3 = 72 ÷ 3 = 24. ::: ------------------------------------------------------------------------ ## Lab 1 Checklist Before you leave today, make sure you have: - [ ] Created a Posit Cloud account - [ ] Run your first arithmetic commands in the Console - [ ] Created a new Quarto document - [ ] Added text and a code chunk to your document - [ ] Successfully rendered the document to HTML - [ ] Saved your file with a clear name ::: callout-tip ## Bonus Challenge Look up the current season scoring stats for **your favorite NFL or NBA team**. Add a new code chunk to your Quarto document that stores three of their recent game scores and calculates the average. Render it and show your instructor! ::: ------------------------------------------------------------------------ ## Before Next Class - Make sure you can log in to Posit Cloud from home - Read **Chapter 2 of Intro2r** (link on Canvas) ::: callout-note ## Where to Find the Textbook All textbooks for this course are **free online**. Go to Canvas → Syllabus → Course Materials to find the links. You never need to buy a textbook for this class. ::: ------------------------------------------------------------------------