Teaching

• Third year at SMU
  • Previously taught ACCT 101
• Before SMU: Taught at the University of Illinois Urbana-Champaign while completing my PhD

Research

• Accounting disclosure: What companies say, and why it matters

What will this course cover?

Learning and getting familiar with R and forecasting

What will this course cover?

Using R for higher level financial forecasting and detection

Datacamp

Datacamp’s tutorials teach R from the ground up, and are mandatory unless you can already code in R.

Textbook

• There is no required textbook
  • Datacamp is taking the place of the textbook
• If you prefer having a textbook…
  • R for Everyone by Jared Lander is a good one
• Other course materials (slides and articles) are available at:
  • eLearn
  • https://rmc.link/acct420
• Announcements will be only on Elearn

Teaching philosphy

1. Analytics is best learned by doing it
   • Less lecture, more thinking
2. Working with others greatly extends learning
   • If you are ahead:
     • The best sign that you’ve mastered a topic is if you can explain it to others
   • If you are lost:
     • Gives you a chance to get help the help you need

Grading

• Standard SMU grading policy
• Participation @ 10%
• Individual work @ 30%
• Group project @ 30%
• Final exam @ 30%

Participation

Outside of class

• Verify your understanding of the material
• Apply to other real world data
  • Techniques and code will be useful after graduation
• Answers are expected to be your own work, unless otherwise stated
  • No sharing answers (unless otherwise stated)
• Submit on eLearn
• I will provide snippets of code to help you with trickier parts

Group project

To be announced later

Final exam

• Why?
  • Ex post indicator of attainment
• How?
  • Likely only 2 hours
  • Long format: problem solving oriented
  • Potentially a small amount of MCQ
• When?
  • Tentatively set for Tuesday, Dec 4 @ 1pm

Expectations

Tech use

• Laptops and other tech are OK!
  • Use them for learning, not messaging
• Examples of good tech use:
  • Taking notes
  • Viewing slides
  • Working out problems
  • Group work
• Avoid:
  • Messaging your friends on Telegram
  • Working on homework for the class in a few hours
  • Watching livestreams of pandas or Hearthstone

Office hours

• Walk-in hours from 10:30-11:30am Fridays
  • Or by appointment
• Short questions can be emailed
  • I try to respond within 24 hours

About you

• Survey at rmc.link/aboutyou
• Results are anonymous
• We will go over the survey next week at the start of class

Learning objectives

What is analytics?

What is analytics?

Oxford: The systematic computational analysis of data or statistics

Webster: The method of logical analysis

Gartner: catch-all term for a variety of different business intelligence […] and application-related initiatives

What is analytics?

Simply put: Answering questions using data

• Additional layers we can add to the definition:
  • Answering questions using a lot of data
  • Answering questions using data and statistics
  • Answering questions using data and computers

Analytics vs AI/machine learning

What are forecasting analytics?

Past and future examples

Past and future examples

Past and future examples

This is where the “educated” comes in

Forecasting analytics in this class

• Revenue/sales
• Shipping delays
• Bankruptcy
• Machine learning applications

What are forensic analytics?

Forensic analytics in this class

• Fraud detection
• Working with textual data
• Detecting changes
• Machine learning applications

Forecasting vs forensic analytics

These are not mutually exclusive. Forensic analytics can be used for forecasting!

In general

53% of companies where using big data in a 2017 survey!

What do companies use analytics for?

What do governments use analytics for?

What do academics use analytics for?

What do academics use analytics for?

What do individuals use analytics for?

Why should you learn analytics?

• Important skill for understanding the world
  • Good timing to learn it, too!
• Gives you an edge over many others
  • Particularly useful for your career
• Jobs for “Management analysts” are expected to expand by 14% from 2016 to 2026
  • Accountants and auditors: 10%
  • Financial analysts: 11%
  • Average industry: 7%
  • All figures from US Bureau of Labor Statistics

What is R?

• R is a “statistical programming language”
  • Focussed on data handling, calculation, data analysis, and visualization
• We will use R for all work in this course

Why do we need R?

• Analytics deals with more data than we can process by hand
  • We need to ask a computer to do the work!
• R is one of the de facto standards for analytics work
  • Third most popular language for data analytics and machine learning (source)
  • Fastest growing of all mainstream languages
  • Free and open source, so you can use it anywhere
  • It can do most any analytics
  • Not a general programming language

Programming in R provides a way of talking with the computer to make it do what you want it to do

Setup

• For this class, I will assume you are using RStudio with the default R installation
  • RStudio downloads
  • R for Windows
  • R for (Max) OS X (Download R-3.5.1.pkg)
  • R for Linux
• You will need a laptop or desktop for this
  • I am working to find a lab on campus for this as well
• For the most part, everything will work the same across all computer types
• Everything in these slides was tested on R 3.5.0 and 3.5.1

How to use R Studio

How to use R Studio

Arithmetic

# Addition uses '+'
1 + 1

## [1] 2

# Subtraction uses '-'
2 - 1

## [1] 1

# Multiplication uses '*'
3 * 3

## [1] 9

# Division uses '/'
4 / 2

## [1] 2

Arithmetic

# Exponentiation uses '^'
5 ^ 5

## [1] 3125

# Modulus (aka the remainder) uses '%%'
46 %% 6

## [1] 4

# Integer division uses '%/%'
46 %/% 6

## [1] 7

Variable assignment

# Store 2 in 'x'
x <- 2

# Check the value of x
x

## [1] 2

# Store arithmetic in y
y <- x * 2

# Check the value of y
y

## [1] 4

Variable assignment

# Previous value of x and y
x

## [1] 2

y

## [1] 4

# Change x, then recheck the value
# of x and y
x <- 200

x

## [1] 200

y

## [1] 4

Application: Singtel’s earnings growth

Set a variable growth to the amount of Singtel’s earnings growth percent in 2018

# Data from Singtel's earnings reports, in Millions of SGD
singtel_2017 <- 3831.0
singtel_2018 <- 5430.3

# Compute growth
growth <- singtel_2018 / singtel_2017 - 1

# Check the value of growth
growth

## [1] 0.4174628

Recap

• So far, we are using R as a glorified calculator
• The key to using R is that we can scale this up with little effort
  • Calculating every public companies’ earnings growth isn’t much harder than calculating Singtel’s!

Scaling this up will give use a lot more value

• We can also leverage functions to automate more complex operations
  • There are many functions built in, and many more freely available
  • We’ll cover this next week
• We’ll also need ways to read data files and work with collections of numbers
  • We’ll cover this next week as well

Wrap up

• R Practice
  • Shortlink: rmc.link/420r1
  • Do the practice here if you would like help with it
  • Otherwise, do it at home
• For next week:
  • Start working on the Datacamp tutorials!
    • Assigned tutorials are on the Datacamp class page
    • For next week, complete the Intro to R course
    • More tutorials will be assigned in future weeks
  • Other helpful tutorials:
    • Rmarkdown tutorial from RStudio