Readings, lectures, etc. | Data Analytics: Learning from Data

Before we start

Tue, 18 Oct 2022 00:00:00 +0000

Data Analytics Survey

We will collect some anonymous student data, so please fill in this quick Data Analytics Survey

Sign up and join course Slack channel

You should have received an invitation to sign up at the course Slack channel. This is where you can ask any questions you have and I will try to respond as quickly as I can. As most questions tend to be similar, it’s always a good idea to have a look at what has already been asked.

If you haven’t received an email, you can use the direct link to sign up for Slack.

Datacamp

You should have received a link to sign up for an account at Datacamp. Please register and complete the following by 17 Oct 2022:
Introduction to the tidyverse course

Software installation

Install R and RStudio on your computer. You can find details on how to install the software here.
We can add to the functionality of base R, by installing a number of packages. We will be using the tidyverse, a collection of packages to help with data manipulation. You can find details on how to install the tidyverse here.

Getting acquainted with Markdown and R Markdown

Throughout the course, we will be using Markdown, a special kind of markup language that lets you format text with simple syntax. You may want to read about markdown here and try out a great interactive markdown tutorial
There is a special kind of markdown document, R Markdown that contains chunks of R code that can be run to produce summary statistics, visualisations, etc, as well as markdown text. R Markdown is the best authoring format for Data Science and allowsus to report, reproduce, and parameterise our work.You can learn more about R Markdown and follow an interactive RMarkdown lesson

Pre-course assignment due on iCorsi on 18 Oct 2022

The aim of the pre-course assignment is to ensure that you successfully install the software, that you get some practice with markdown, and that you are able to knit an R Markdown (.Rmd) document into an HTML file.

Specifically, you need to:

Write a short biography using markdown. You can use a Visual Editor that lets you use markdown much like Microsoft Word, by clicking on the Visual button, rather than the default Source button when editing your work in RStudio.
Fill out the code in the empty chunks provided, (you can definitely copy, paste, and adapt from tutorials!), and answer all questions.
Knit the Rmd to an HTML file
Upload to Canvas the knitted HTML file

You can download pre-programme files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

install.packages("usethis")
usethis::use_course("https://github.com/kostis-christodoulou/usi_EMBA_analytics/archive/refs/heads/master.zip")

Further Resources on ggplot

In our first steps with the tidyverse, we will learn how to visualise data.

Besides the courses, please try out this Data Visualization Primer.
Once you complete the primer, you may want to read through the visualisation examples and have a go at the visualisation exercises contained in this website.

Introduction to Regression Models

Sun, 24 Oct 2021 00:00:00 +0000

Readings

ModernDive Chapters 5-6

Session Files

You can download all session files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

usethis::use_course("https://github.com/kostis-christodoulou/bit2021/raw/usi_EMBA_analytics/session5-lecture3.zip")

Workshop on regression

Sun, 24 Oct 2021 00:00:00 +0000

Readings

Readings

ModernDive Chapter 10.2-10.3

Sampling; Probability Distributions

Sat, 23 Oct 2021 00:00:00 +0000

Readings

Session Files

You can download all session files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

usethis::use_course("https://github.com/kostis-christodoulou/usi_EMBA_analytics/raw/master/session3-lecture2.zip")

Workshop 2: Confidence Intervals; hypothesis testing

Sat, 23 Oct 2021 00:00:00 +0000

Readings

Questions to reflect on

In the Bertrand and Mullainathan (2004) experiment, the authors randomly assigned first names, and thus race and gender, to fictitious candidate resumes submitted to online job ads. Since other candidate attributes and overall candidate quality were assigned independent of name, the authors wanted to measure differences in callback rates for interviews.
- Would you expect to see any statistical differences in callback rates between races? The authors state that Job applicants with white names needed to send about 10 resumes to get one callback; those with African-American names needed to send around 15 resumes to get one callback.

Session Files

You can download all session files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

usethis::use_course("https://github.com/kostis-christodoulou/usi_EMBA_analytics/raw/master/session4-workshop2.zip")

Exploratory Data Analysis

Fri, 15 Oct 2021 00:00:00 +0000

Class Video

Readings

The syllabus for this class
ModernDive Chapters 1 and 2
Study: Charts change hearts and minds better than words do

Questions to reflect on

2021 Student Survey contains data from an anonymous online survey of postgraduate students. How would we describe the shape, centre, and spread of the following variables:
- height, a respondent’s height in cm
- exercise_hours, number of hours exercising last week
- online_hours, number of hours spent online last week
- handedness, an indicator from -1 (exclusively left handed) to 0 (ambidextrous) to +1 (exclusively right handed)
- haircut_spend, amount of money spent on last haircut, expressed in USD$.

Session Files

Slides for today’s session are available on Canvas.
You can download all session files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

install.packages("usethis")
usethis::use_course("https://github.com/kostis-christodoulou/usi_EMBA_analytics/raw/master/session1-lecture1.zip")

Workshop 1: Import, visualise, and manipulate data

Fri, 15 Oct 2021 00:00:00 +0000

Class Video

Readings

ModernDive Chapters 2-3
Hans Rosling, “200 Countries, 200 Years, 4 Minutes”
R4DS Chapter 11, Data Import
R4DS Chapter 5, Data transformation
Chapter 2 in Claus Wilke, Fundamentals of Data Visualization
Chapter 3 in Kieran Healy, Data Visualization

Questions to reflect on

What data was mapped to which aesthetics in Rosling’s video?
What data would you need to create the bar plot in NYT’s article?

Session Files

You can download all session files (data, code, etc.) by pulling from course Github repo. Alternatively, please install package usethis. Once you have it, you can download, unzip, and open everything within an RStudio project by typing the following in the RStudio console

usethis::use_course("https://github.com/kostis-christodoulou/usi_EMBA_analytics/raw/master/session2-workshop1.zip")

Readings, lectures, etc. | Data Analytics: Learning from Data

Before we start

Data Analytics Survey

Sign up and join course Slack channel

Datacamp

Software installation

Getting acquainted with Markdown and R Markdown

Pre-course assignment due on iCorsi on 18 Oct 2022

Further Resources on ggplot

Introduction to Regression Models

Readings

Session Files

Workshop on regression

Readings

Sampling; Probability Distributions

Readings

Session Files

Workshop 2: Confidence Intervals; hypothesis testing

Readings

Questions to reflect on

Session Files

Exploratory Data Analysis

Class Video

Readings

Questions to reflect on

Session Files

Workshop 1: Import, visualise, and manipulate data

Class Video

Readings

Recommended

Questions to reflect on

Session Files