STAT 385 Summer 2025 - Public-Facing Website

Written on June 13th, 2025 by Christopher Kinson

STAT 385 Statistics Programming Methods

3 Credit Hours - Major Elective

Section ONL

Summer 2025 - Public-Facing Website

Table of Contents

• Week 1
• Week 2
• Week 3
• Week 4
• Week 5
• Week 6
• Week 7
• Week 8

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Week 1

This is the first week of class. It is of critical importance you read the syllabus, especially the Software section to download and install necessary technologies: R, RStudio Desktop, and Git. We begin with an introductory exploration of R, RStudio, and Git. There are various objects in R that are foundational to our ability to program. Each R object has associated properties and purposes. These objects may be of different types and modes. We use R via the integrated development environment, RStudio Desktop. It is a helpful, user-friendly layout space for programming and creating various files. RStudio works with .R script files and reproducible document files such as .Rmd and can knit a reproducible document to .html and other formats. Git and GitHub are critical to submitting assignments in this course. Each student has a repo in this course that they made via following the instructions of the syllabus Software section Step 2. Create a GitHub account if you don’t have one already and Sign into GitHub, Step 3. Click here to enroll in STAT 385 course organization and follow the steps to be setup properly in the learning management system. Each repo has a main branch, which serves as the landing page of the repo. We will place files into directories on the main branch of our repos. For example, when you complete homework01, you will submit it into the homework directory. Grades will be returned to students on a grades branch for the corresponding week. Because of the file organization on branches, it’s important to learn about Git commands and how to navigate the branches.

The following are readings which will be helpful in first learning the course material for this week.

1. Bryan’s Why Git? Why GitHub?

2. Sanchez’s First Contact with R via RStudio

3. Sanchez’s First Contact with RStudio

4. Bryan’s Git Commands

5. Bryan’s Git Branches

6. Gagolewski’s Preface

After completing the readings, we encourage students to begin watching the lecture videos below.

• Prof. Kinson’s introduction, Explanation of background and pedagogy, Introducing STAT 385 Summer 2025

• Highlights of the syllabus

• Getting setup in the course with the software, The importance of downloading and installing R, RStudio, and Git, Using the Terminal

• Using R for the first time, working with .R script files, The importance of keeping your version of R up to date

• Using RStudio for the first time, The importance of R’s documentation and RStudio’s Help pane to learn about R functions and objects

• The importance of version control software like Git, Saving, saving as, and renaming files, Comparing/contrasting local file storage and version control

• Installing Git on MacOS via Homebrew, The importance of creating a GitHub account using an email that you frequently check

• Customizing the appearance of the Terminal on MacOS, Customizing the appearance of RStudio, Customizing the settings of RStudio to save memory and start in clean sessions, Reproducibility

• Enroll in STAT 385 course organization in GitHub via repo creator (Step 3), Uploading a file i.e. Submitting an assignment via GitHub, Authenticating your Github acccount

• Cloning your repo, Navigating file system with shell commands, Submitting an assignment via Git commands

• Explaining the importance of an .Rmd file and its code chunks, Key R functions for Week 1)

• More key R functions for Week 1, Vectorization vs summarization, Practice submitting an assignment via Git commands

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week01

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, June 20, 2025.

1. gdp01

2. homework01

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 02:00 pm - 3:00 pm in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

• Special One Time Only - Professor Kinson’s Office Hour on Friday 06:30 pm - 07:30 pm in Zoom

---

Week 2

This week we acknowledge that we have an introductory understanding of R, RStudio, and Git. This week, we dive more into R. There are various objects in R and vectors are among the simplest of R’s objects. These vectors are atomic meaning they are of a single type - logical, numeric, character, complex, raw. Each object has associated properties, such as mode and length, which we may later call attributes. Vectors can be indexed or subset based on vectors of various types. Types can be changed implicitly (coercion) and explicitly (type casting) in R. Additional key R functions are discussed in the lecture videos.

The following are readings which will be helpful in first learning the course material for this week.

1. Sanchez’s First Contact with Vectors

2. Sanchez’s Properties of Vectors

3. Sanchez’s Creating Vectors

4. Sanchez’s More About Vectors

5. Venables et al’s Simple manipulations; numbers and vectors

6. Venables et al’s Objects, their modes and attributes

After completing the readings, we encourage students to begin watching the lecture videos below.

• Review of submitting an assignment via Git from the command line, Verifying that the file is submitted in your repo in GitHub

• Object attributes including length and mode, Types of atomic vectors, Consistency of quotation marks, Implicit coercion, Testing of types

• Missing values, null values, and numerically undefined types, Changing a vector’s length

• Removing and assigning objects, Index vectors and subsetting a vector, Logical operators and comparison operators, Key R functions, Defining a recursive object

• More examples of index vectors and subsetting a vector, More key R functions for Week 2

• More key R functions for Week 2

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week02

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, June 27, 2025.

1. gdp02

2. homework02

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 3

In this week, we introduce other objects - matrices, arrays, factors, lists, and data frames. These objects are critical for working with R and considering how data can be accessed. Some objects are atomic, e.g., matrix() and factor(), while others are recursive, e.g., list() and data.frame(). Some objects are basic, e.g., list(), while others are compound, e.g., matrix(), factor(), data.frame(). Matrices are a special type of array - a two-dimensional array. Arrays are of general dimension such that the user must specify the dimension and its attributes. Lists are generic vectors meaning that they are very flexible. Lists are recursive objects too in the sense that they can contain lists themselves. In R, data frames are always lists, but lists are not always data frames. Additional key R functions are discussed in the lecture videos.

The following are readings which will be helpful in first learning the course material for this week.

1. Sanchez’s Matrices and Arrays

2. Gagolewski’s Lists and attributes

3. Sanchez’s More About Matrices

4. Sanchez’s Factors

5. Sanchez’s Lists

6. Sanchez’s Data frames

After completing the readings, we encourage students to begin watching the lecture videos below.

• The importance of learning the various objects in R, General descriptions of arrays, matrices, factors, Demonstrating factors

• Key R functions for Week 3

• More key R functions for Week 3, Recycling in R

• Lists, Named and unnamed components of lists, Boxing and unboxing a list, Subsetting a list

• Data frames, Attributes of data frames, Comparing lists and data frames

• Matrices and arrays, Attributes of matrices and arrays

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week03

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, July 4, 2025.

1. gdp03

2. homework03

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 4

We’ve covered several data objects or structures used in R. Now we move into certain flows of programming including conditionals (if and else) and loops (for and while). We also discover some potential problems with naively created loops and objects. Burn’s informs us that growing objects in R costs us memory and time, which can have devastating effects in programming efficiency. With these flows and well-understood objects, we can add specific efficient repetition to our programming. And there is power in repetition for us as statisticians. Additionally, we cover common regular expression syntax and R functions - some that employ regex and some that do not - to manipulate character vectors.

The following are readings which will be helpful in first learning the course material for this week.

1. Sanchez’s Conditionals: If-Else

2. Sanchez’s Iterations: For Loop

3. Sanchez’s Iterations: While Loop

4. Burns’s Growing Objects

5. Gagolewski’s Data frames

6. Gagolewski’s Character vectors

After completing the readings, we encourage students to begin watching the lecture videos below.

• If and else statements, Grouped expressions, The any() and all() functions, else, and ifelse,

• The ifelse() function is vectorized

• The for loop, Combining if and else with for loop, The break statement

• The while loop, How to stop the while loop, The repeat loop and breaking out of it

• Using regular expression syntax with relevant R functions, Using the grepl() function with regex syntax to detect characters

• Using the strsplit() function to split up characters, Using the substring() function to extract characters based on position, Key R functions for Week 4

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week04

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, July 11, 2025.

1. gdp04

2. homework04

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 5

This week, the readings cover how to define custom functions and common pitfalls of the concept vectorization. There is also an in-the-weeds discussion of R’s environments and how to take advantage of that knowledge when creating objects and functions in R. User-defined functions are critical for building programs in R. Programs are essentially big functions that likely have considerate user-friendliness in their design. It is a good idea to practice making user-defined functions often during this chapter. Learners are encouraged to try all exercises in the readings for practice.

The following are readings which will be helpful in first learning the course material for this week.

1. Burns’s Failing to Vectorize

2. Burns’s Over-Vectorizing

3. Sanchez’s Intro to Functions

4. Sanchez’s Expressions

5. Sanchez’s More About Functions

6. Grolemund’s Environments

7. Gagolewski’s Functions

After completing the readings, we encourage students to begin watching the lecture videos below.

• The importance of learning about R objects and important principles of recycling, vectorization, and summarization, Creating a user-defined function

• One big goal is to create a vectorized median function, Map() vs lapply() functions, creating a sample function for data frames

• Key R functions for Week 5, Continuing to create a vectorized median function

• Remembering to keep it simple when programming, continuing to create a vectorized median function, More key R functions for Week 5, Comparing the output of the vectorized median function with existing vectorized mean function

• Adjusting vectorized median function output to align with R’s vectorized mean function, Creating a vectorized character-counting function for a specified character, Avoiding using existing R object names,

• Breaking down a complex problem by first tackling simpler piecewise problems, Continuing to create a vectorized character-counting function for a specified character

• Split-apply-combine concept and strategy, Using the split(), Map(), and do.call() functions

• Checking output type for do.call() function, The more you know, the more you can imagine what is possible

• Explaining Grolemund’s Enironments chapter, Knowing how to work with R’s environments is useful when your intentions as a programmer are clear, Recreating playing cards for a standard deck and uno deck, Which environment is active, runtime, parent, origin, or calling for functions and objects, Using the assign() function to create objects that exist in a specified environment, Extending Grolemund’s custom shuffle function as an example, More key R functions for Week 5

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week05

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, July 18, 2025.

1. gdp05

2. homework05

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 6

By now, we go even deeper in the weeds to understand R’s S3 system and how to consider more than just coding results when it comes to programs. The reading materials are less coding heavy, except programs, but discuss important ideas about R’s internal workings that help us understand what’s underneath programs.

The following are readings which will be helpful in first learning the course material for this week.

1. Grolemund’s Programs

2. Grolemund’s S3

3. Gagolewski’s S3 Classes

After completing the readings, we encourage students to begin watching the lecture videos below.

• Overview concepts: programs, S3 system, functions are recursive

• Creating a custom user-defined function that collapses strings together into a single length one character vector

• Comparing and contrasting the print() and cat() functions, Being open to new information that we don’t already know has lifelong benefits

• Explaining Grolemund’s slot machine game and why object structure matters, Comparing vector with attributes object to list with names object, Naively printing text in a pretty way comes at a cost

• Explaining Grolemund’s slot machine game and its advantages with the S3 system, Creating a print method for a custom class

• Creating a print method for a custom class - comparing vector with attributes object to list with names object

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week06

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, July 25, 2025.

1. gdp06

2. homework06

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 7

This is the penultimate week of the course. The readings are less coding intensive, but do challenge learners to think, be curious, and push the limits of their creativity. The human brain is capable of doing so many things. Have you considered how much your brain does even when you are asleep? Design, intentionm, and alignment are a part of what can be the difference between a good program and a great one. Learners are encouraged to ask questions, read and gather information, and make fun games for the final project.

The following are readings which will be helpful in first learning the course material for this week.

1. Gagolewski’s Designing functions

2. Kinson’s Slides on Weston’s Creativity for Critical Thinkers

3. Kanna’s ‘How to Solve Coding Problems with a Simple Four-Step Method’

After completing the readings, we encourage students to begin watching the lecture videos below.

• Principles and strategies of coding and programming, Designing a game by considering the options and cases, Can you create a game with a quit mechanism?, Setting up an .R script file to be executed via the source() function

• Using the source() function to run a local .R script file, Local files are not reproducible

After watching the lecture videos, we encourage students to read the notes which serve as highlights of important concepts based on the readings and lecture videos. The notes are below.

• key-functions-week07

After reading, watching, and digesting the course materials above, we encourage students to begin the assignments of the week. Below you will find the two assignments, which are due at 11:59 pm on Friday, August 1, 2025.

1. gdp07

2. homework07

Remember that the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

---

Week 8

This is the last week of the course. There is no new material for this week. Learners are encouraged to spend ample time working and fine-tuning their final projects for this course. Review the final project guidelines and grading rubric.

We encourage students to watch the lecture videos below and review videos from all previous weeks.

After watching the lecture videos, we encourage students to re-read the notes and practice code therein as it may be helpful when creating the final project .R file.

Because the final project is the only assignment left and due at 11:59 pm on Friday, August 8, 2025, we encourage students to review the final project details.

Although this is the last week of the semester, the course staff, i.e. Professor Christopher Kinson and TA Lam Lam Hui, are still here to help and educate. The following are opportunities for learners to get help in their learning and skill building ordered by day of the week.

• TA Hui’s Office Hour on Tuesday 09:00 am - 10:00 am in Zoom

• Course Staff Forum Hour on Wednesday 06:30 pm - 07:30 pm in Zoom

• Professor Kinson’s Office Hour on Thursday 06:30 pm - 07:30 pm in Zoom

• TA Hui’s Office Hour on Friday 09:00 am - 10:00 am in Zoom

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  STAT 385 Summer 2025 Syllabus