Instructions

This checklist confirms that you have completed all the technical setup required for EPI 553. This assignment is graded for completion only and should take 30-45 minutes to complete.

How to Use This Checklist: 1. Work through each section below 2. Mark items as complete as you verify them 3. Answer the reflection questions 4. Save this document with your name (e.g., LastName_FirstName_Setup_Checklist.Rmd) 5. Knit to HTML (Ctrl+Shift+K) 6. Upload the HTML file to Brightspace by January 29, 2026

Section 1: R & RStudio Installation

Objective: Verify that R and RStudio are installed and up-to-date.

# Run this code to check your R installation
cat("R Version:", paste(R.version$major, R.version$minor, sep="."), "\n")

## R Version: 4.5.2

cat("Platform:", R.version$platform, "\n")

## Platform: aarch64-apple-darwin20

Completion checklist:

R is installed (version 4.0 or later)
- If older than 4.0, download from https://www.r-project.org/
RStudio is installed and functional
- Check: Help → About RStudio
- Current version shown: _________________________
You can open and read this document in RStudio
You successfully ran the R code above without errors

Reflection Question 1: What version of R and RStudio are you running? (Screenshot or write the versions below)

Your answer:

Version info here...

Section 2: Required Packages

Objective: Verify that all required packages are installed and load without errors.

# This code checks and loads required packages
required_packages <- c(
  "tidyverse", "rmarkdown", "knitr", "ggplot2", "dplyr", 
  "car", "lmtest", "sandwich", "stargazer", "broom"
)

cat("Loading required packages...\n\n")

## Loading required packages...

all_loaded <- TRUE
for (pkg in required_packages) {
  tryCatch({
    library(pkg, character.only = TRUE)
    cat("✓", pkg, "loaded successfully\n")
  }, error = function(e) {
    cat("✗", pkg, "FAILED to load\n")
    all_loaded <<- FALSE
  })
}

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.1     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.2
## ✔ purrr     1.2.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

## ✓ tidyverse loaded successfully
## ✓ rmarkdown loaded successfully
## ✓ knitr loaded successfully
## ✓ ggplot2 loaded successfully
## ✓ dplyr loaded successfully

## Loading required package: carData
## 
## Attaching package: 'car'
## 
## The following object is masked from 'package:dplyr':
## 
##     recode
## 
## The following object is masked from 'package:purrr':
## 
##     some

## ✓ car loaded successfully

## Loading required package: zoo
## 
## Attaching package: 'zoo'
## 
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## ✓ lmtest loaded successfully
## ✓ sandwich loaded successfully
## ✗ stargazer FAILED to load
## ✓ broom loaded successfully

cat("\n")

if (all_loaded) {
  cat("✓ All packages loaded successfully!\n")
} else {
  cat("⚠ Some packages failed. Run the code in Appendix A to install them.\n")
}

## ⚠ Some packages failed. Run the code in Appendix A to install them.

Completion checklist:

All 10 packages loaded without errors
- If any failed, run the installation code in Appendix A and try again
You restarted R after installing packages (Ctrl+Shift+F10 in RStudio)
All packages loaded successfully on second attempt

Reflection Question 2: Did any packages fail to load initially? If yes, which ones and how did you resolve it?

Your answer:

Answer here...

Section 3: Working Directory & Project Structure

Objective: Set up your project directory with proper folder organization.

# Check current working directory
cat("Your current working directory:\n")

## Your current working directory:

cat(getwd(), "\n\n")

## /Users/mm992584/Library/CloudStorage/OneDrive-UniversityatAlbany-SUNY/Spring 2026/Epi 553/Week 1 R Setup Chunk

# Check for R Project file
if (file.exists(".Rproj")) {
  cat("✓ R Project file (.Rproj) detected\n")
} else {
  cat("⚠ No R Project file found\n")
  cat("   Create one: File → New Project → New Directory\n")
}

## ⚠ No R Project file found
##    Create one: File → New Project → New Directory

# Check for suggested folders
cat("\nFolder structure check:\n")

## 
## Folder structure check:

folders <- c("data", "scripts", "outputs", "figures")
for (folder in folders) {
  if (dir.exists(folder)) {
    cat("✓", folder, "/ exists\n")
  } else {
    cat("○", folder, "/ (needs to be created)\n")
  }
}

## ○ data / (needs to be created)
## ○ scripts / (needs to be created)
## ○ outputs / (needs to be created)
## ○ figures / (needs to be created)

Completion checklist:

Working directory is set to your course project folder
- Path: ________________________________________________
R Project file (.Rproj) exists in your project directory
Four folders exist: data/, scripts/, outputs/, figures/
- Run this code if folders are missing:
```
dir.create("data")
dir.create("scripts")
dir.create("outputs")
dir.create("figures")
```
You can navigate between these folders in RStudio’s Files pane

Reflection Question 3: Describe your folder structure. What is the full path to your project directory?

Your answer:

Example: /Users/jsmith/Documents/Albany/EPI553

Your path:

Section 4: R Markdown & Rendering

Objective: Confirm you can create, edit, and render R Markdown documents.

# Verify R Markdown package
if (require("rmarkdown", quietly = TRUE)) {
  cat("✓ rmarkdown package is installed and loaded\n")
  cat("✓ You can render to HTML, PDF, and Word formats\n\n")
  cat("To render a document:\n")
  cat("1. Click the 'Knit' button (top of editor) or press Ctrl+Shift+K\n")
  cat("2. Select output format (HTML, PDF, Word)\n")
  cat("3. View the rendered document in RStudio Viewer\n")
} else {
  cat("✗ rmarkdown not found. Run: install.packages('rmarkdown')\n")
}

## ✓ rmarkdown package is installed and loaded
## ✓ You can render to HTML, PDF, and Word formats
## 
## To render a document:
## 1. Click the 'Knit' button (top of editor) or press Ctrl+Shift+K
## 2. Select output format (HTML, PDF, Word)
## 3. View the rendered document in RStudio Viewer

Completion checklist:

You can see the “Knit” button at the top of this document in RStudio
You have successfully rendered an R Markdown file to HTML
- Document rendered: ____________________________________
- Date/time rendered: ___________________________________
The rendered HTML file opened automatically in the RStudio Viewer
You can save the rendered HTML file to your outputs/ folder

Reflection Question 4: Describe the process you followed to render this checklist to HTML. What did you click and what happened?

Your answer:

Answer here...

Section 5: File Management & Uploads

Objective: Practice saving files and uploading to Brightspace.

Completion checklist:

You know where files are saved on your computer
- Primary save location: _____________________________
You can navigate to files using Windows Explorer or Finder
You saved this document with a clear filename: LastName_FirstName_Setup_Checklist.Rmd
You rendered it to HTML: LastName_FirstName_Setup_Checklist.html
You can locate the rendered HTML file on your computer
- Full file path: ______________________________________
You have logged into Brightspace and found the assignment submission area
You know how to upload a file to Brightspace (done or ready to do)

Reflection Question 5: What is the exact filename (including .html extension) of the rendered version of this document?

Your answer:

Example: Smith_John_Setup_Checklist.html

Your filename:

Section 6: Data & Code Practice

Objective: Verify you can work with data and run code in R.

Let’s do a quick practice analysis:

# Load data
library(tidyverse)

# Use built-in mtcars dataset
cat("Dataset: mtcars (Motor Trend Car Road Tests)\n")

## Dataset: mtcars (Motor Trend Car Road Tests)

cat("Sample of data:\n")

## Sample of data:

print(head(mtcars, 3))

##                mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4     21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710    22.8   4  108  93 3.85 2.320 18.61  1  1    4    1

cat("\n\nBasic Summary Statistics:\n")

## 
## 
## Basic Summary Statistics:

summary(mtcars$mpg)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.40   15.43   19.20   20.09   22.80   33.90

Create a simple visualization:

mtcars %>%
  ggplot(aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point(size = 3, alpha = 0.7) +
  geom_smooth(method = "lm", se = FALSE, alpha = 0.5) +
  labs(
    title = "Fuel Efficiency vs Weight",
    subtitle = "EPI 553 - Setup & Workflow Checklist",
    x = "Weight (1000 lbs)",
    y = "Miles Per Gallon (mpg)",
    color = "Cylinders"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 14, face = "bold"),
    legend.position = "bottom"
  )

Fit a regression model:

# Fit a simple linear regression model
model <- lm(mpg ~ wt + factor(cyl), data = mtcars)

cat("Linear Regression Model: mpg ~ weight + cylinders\n\n")

## Linear Regression Model: mpg ~ weight + cylinders

print(summary(model))

## 
## Call:
## lm(formula = mpg ~ wt + factor(cyl), data = mtcars)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.5890 -1.2357 -0.5159  1.3845  5.7915 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   33.9908     1.8878  18.006  < 2e-16 ***
## wt            -3.2056     0.7539  -4.252 0.000213 ***
## factor(cyl)6  -4.2556     1.3861  -3.070 0.004718 ** 
## factor(cyl)8  -6.0709     1.6523  -3.674 0.000999 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.557 on 28 degrees of freedom
## Multiple R-squared:  0.8374, Adjusted R-squared:   0.82 
## F-statistic: 48.08 on 3 and 28 DF,  p-value: 3.594e-11

# Extract key results
cat("\n\nKey Results:\n")

## 
## 
## Key Results:

cat("R-squared:", round(summary(model)$r.squared, 4), "\n")

## R-squared: 0.8374

cat("Residual Std. Error:", round(summary(model)$sigma, 4), "\n")

## Residual Std. Error: 2.5569

Completion checklist:

Data loaded successfully (mtcars)
Summary statistics displayed without errors
Plot rendered correctly showing relationship between weight and mpg
Regression model ran successfully and displayed results

Reflection Question 6: Looking at the plot above, describe the relationship between vehicle weight (x-axis) and fuel efficiency (y-axis). What does the model suggest?

Your answer:

Answer here...

Final Completion Checklist

Use this final checklist to confirm you’ve completed everything:

Item	Status	Notes
✓ Completed all 6 sections above	☐
✓ Answered all 6 reflection questions	☐
✓ Successfully rendered this document to HTML	☐
✓ Saved rendered HTML with correct filename	☐
✓ Ready to upload to Brightspace	☐

Submission Instructions

For this course, you will submit your work in two ways:

Upload to Brightspace (for grading)
Publish to RPubs (for portfolio & reproducibility)

Option A: Upload to Brightspace

Save, Render, and Submit:

Save this document with your name: LastName_FirstName_Setup_Checklist.Rmd
Render to HTML by clicking “Knit” (Ctrl+Shift+K)
- Output file: LastName_FirstName_Setup_Checklist.html
Upload to Brightspace:
- Go to: EPI 553 → Assignments → Week 1 Setup & Workflow Checklist
- Click “Submit Assignment”
- Upload the HTML file
- Add any additional notes if needed
- Click “Submit”

Deadline: January 29, 2026

Option B: Publish to RPubs (Recommended - Builds Your Portfolio!)

Publishing to RPubs demonstrates your reproducible research skills and creates a professional portfolio. This is optional but strongly encouraged.

Why Publish to RPubs?

Build a public portfolio of your work
Show employers your data analysis skills
Practice reproducible research practices
Share your work transparently

Step-by-Step: Publishing to RPubs

Step 1: Create an RPubs Account (One-Time Only)

Go to https://rpubs.com/
Click “Register” in the top right
Choose a professional username (e.g., lastname_firstname or ualbany_ID)
- Avoid spaces and special characters
- This appears in your public URLs
Enter your email and password
Click “Register”
Confirm your email via the link sent to your inbox

Step 2: Connect RStudio to Your RPubs Account

Open RStudio
Go to Tools → Global Options
Click “Publishing” in the left menu
Click the “Connect…” button
Select “RPubs”
Log in with your RPubs credentials
Click “Authorize”
Return to RStudio when finished

Step 3: Render and Publish

Render this document: Click “Knit” button (Ctrl+Shift+K)
Publish: Once rendered, look for the blue “Publish” button in the Viewer pane (top right)
- Alternative: Click ▼ next to “Knit” → “Publish Document”
Configure Your Publication:
- Platform: Select “RPubs”
- Title: EPI 553: Week 1 Setup Checklist - LastName
- Slug (URL ID): epi553_week1_setup_lastname
Click “Publish”
- RPubs processes your document
- Your document is now live and public!
- You’ll see your unique RPubs URL

RPubs Best Practices

Professional Presentation: - Include your full name as the author - Use consistent slug naming: epi553_weekN_lastname - Add course number and date to the title - Update your publication when making corrections

Privacy & Professionalism: - RPubs documents are public by default - Only publish work you’re comfortable sharing - Never include sensitive or confidential data - Your username is visible in the URL (keep it professional!)

Building Your Portfolio: - Organize chronologically in your RPubs profile - Link from your CV, resume, or GitHub - Shows employers your data analysis skills - Demonstrates commitment to reproducible research

Troubleshooting RPubs Publishing

Problem: “Publish button is greyed out” - Make sure output format is html_document - Check YAML header at top of file - Try rendering again (Ctrl+Shift+K)

Problem: “Cannot connect to RPubs” - Verify internet connection - Re-authorize in Tools → Global Options → Publishing - Clear RStudio cache: Tools → Global Options → Clear All

Problem: “Document failed to publish” - Check document size (limit ~25MB) - Ensure no broken links in your document - Try again in a few minutes

Need Help? - RPubs documentation: https://rpubs.com/about/getting-started - RStudio guide: https://posit.co/blog/r-markdown-and-rpubs/ - Contact Dr. Masum or Yiming Wang during office hours

Summary: Both Submissions

Method	Purpose	Required?
Brightspace	Grade submission	Yes
RPubs	Professional portfolio	Strongly encouraged

You will submit: 1. Required: HTML file to Brightspace 2. Optional but recommended: RPubs link to Brightspace comments

Troubleshooting

R & RStudio Issues

Quick Issues:

“Cannot find package X”
- Run: install.packages("package_name")
- Make sure you’re connected to the internet
“Object not found”
- Make sure you ran all code chunks above in order
- Try running code manually in the console
Plot doesn’t show
- Check that ggplot2 loaded correctly
- Verify all required packages are installed
Knit button missing
- Make sure this is a .Rmd file, not .R
- Click in the document first, then look for Knit button
Firewall blocking package downloads
- Connect to UAlbany WiFi or use VPN
- Try installing with: install.packages(pkg, type = "source")

RPubs Publishing Issues

Common Problems:

“Publish button is greyed out”
- Make sure output format is html_document
- Check YAML header has correct formatting
- Try rendering again (Ctrl+Shift+K)
“Cannot connect to RPubs”
- Check your internet connection
- Re-authorize: Tools → Global Options → Publishing → Connect
- Clear RStudio cache if persistent
“Publishing failed” error
- Check document size (should be under 25MB)
- Ensure no broken links in your code or text
- Try publishing again in a few minutes
- Check that your username contains no spaces
“Already published to this slug”
- Use a different slug/URL name
- Or republish to update existing document

Still Having Trouble?

For R/RStudio Help: - UAlbany IT Help Desk: 518-442-3700 or helpdesk@albany.edu - Office hours with Dr. Masum or Yiming Wang

For RPubs Help: - RPubs documentation: https://rpubs.com/about/getting-started - RStudio publishing guide: https://posit.co/blog/r-markdown-and-rpubs/

For Course Content Questions:

Instructor (Dr. Muntasir Masum): - Email: mmasum@albany.edu - Office: Pine Bush 255 - Office Hours: Tuesdays & Thursdays, 10:20 am - 11:30 am

Teaching Assistant (Yiming Wang): - Email: ywang98@albany.edu - Office Hours: Mondays & Wednesdays, 11:30 am - 4:30 pm

Please reach out by January 27 if you have persistent issues!

Appendix A: Installing Packages (If Needed)

If packages failed to load in Section 2, run this code:

# Install all required packages
required_packages <- c(
  "tidyverse", "rmarkdown", "knitr", "ggplot2", "dplyr", 
  "car", "lmtest", "sandwich", "stargazer", "broom"
)

# Install each package
for (pkg in required_packages) {
  if (!require(pkg, character.only = TRUE)) {
    cat("Installing", pkg, "...\n")
    install.packages(pkg, dependencies = TRUE)
  }
}

cat("\n✓ Installation complete!\n")
cat("Now restart R: Ctrl+Shift+F10\n")
cat("Then reload this document and try Section 2 again.\n")

Appendix B: Creating Folders (If Needed)

If you need to create the folder structure, run this code in the R Console:

# Create folders if they don't exist
if (!dir.exists("data")) {
  dir.create("data")
  cat("✓ Created data/ folder\n")
}

if (!dir.exists("scripts")) {
  dir.create("scripts")
  cat("✓ Created scripts/ folder\n")
}

if (!dir.exists("outputs")) {
  dir.create("outputs")
  cat("✓ Created outputs/ folder\n")
}

if (!dir.exists("figures")) {
  dir.create("figures")
  cat("✓ Created figures/ folder\n")
}

cat("\nAll folders created successfully!\n")

Successfully completing this checklist means you are ready for Week 1 of EPI 553!

For questions or concerns, reach out to Dr. Masum or Yiming Wang.

Good luck! 🎓

EPI 553: Setup & Workflow Checklist

Principles of Statistical Inference II (Spring 2026)

Muntasir Masum

Due by: End of Week 1 (January 29, 2026)

Instructions

Section 1: R & RStudio Installation

Section 2: Required Packages

Section 3: Working Directory & Project Structure

Section 4: R Markdown & Rendering

Section 5: File Management & Uploads

Section 6: Data & Code Practice

Final Completion Checklist

Submission Instructions

Option A: Upload to Brightspace

Option B: Publish to RPubs (Recommended - Builds Your Portfolio!)

Why Publish to RPubs?

Step-by-Step: Publishing to RPubs

Step 1: Create an RPubs Account (One-Time Only)

Step 2: Connect RStudio to Your RPubs Account

Step 3: Render and Publish

RPubs Best Practices

Troubleshooting RPubs Publishing

Summary: Both Submissions

Troubleshooting

R & RStudio Issues

RPubs Publishing Issues

Still Having Trouble?

Appendix A: Installing Packages (If Needed)

Appendix B: Creating Folders (If Needed)

EPI 553: Setup & Workflow Checklist

Principles of Statistical Inference II (Spring 2026)

Muntasir Masum

Due by: End of Week 1 (January 29, 2026)

Instructions

Section 1: R & RStudio Installation

Section 2: Required Packages

Section 3: Working Directory & Project Structure

Section 4: R Markdown & Rendering

Section 5: File Management & Uploads

Section 6: Data & Code Practice

Final Completion Checklist

Submission Instructions

Option A: Upload to Brightspace

Option B: Publish to RPubs (Recommended - Builds Your Portfolio!)

Why Publish to RPubs?

Step-by-Step: Publishing to RPubs

Step 1: Create an RPubs Account (One-Time Only)

Step 2: Connect RStudio to Your RPubs Account

Step 3: Render and Publish

Step 4: Share Your RPubs Link

RPubs Best Practices

Troubleshooting RPubs Publishing

Summary: Both Submissions

Troubleshooting

R & RStudio Issues

RPubs Publishing Issues

Still Having Trouble?

Appendix A: Installing Packages (If Needed)

Appendix B: Creating Folders (If Needed)