• Appreciate the role of Data Visualization in various domains
  
• identify good and bad visualizations, and the criteria to critique
• Select the appropriate visualization for  a specific purpose
• Use various tools and techniques to construct a range of visualizations for both exploration and explanation
• Learn to "tell a story" about your data using visualization

• For the Intro to Data Visualization module of the course, links are provided in the Course Schedule and on Sakai under the appropriate topic.  Some important links include:
  
• Tufte's Design Principles
  and here
• http://flowingdata.com
• list of some data visualization sites
• One of many data visualization checklists.

• For the R module of the course, below are the main links (in effect, the "text" for this part of the cousre).  Additional links are posted in Course Schedule or Sakai topic.
• Jared Lander.  R for Everyone, Advanced Analytics and Graphics 2nd edition, Addison-Wesley, 2017.  ISBN-13:  978-0134546926.   You do not need to buy the book.  There is a free 48-page preview of the first edition available at the Pearson site.   There are also many sites online where you can sign up to be able to download a pdf.  However, I walked through many examples that are inspired by this text.
• Alboukadel Kassambara.  Guide to Create Beautiful Graphics in R,  STHDA, 2013.  isbn:  9781532916960.  Most examples, with small modifications, are available on his wonderful website and his R support website.  Although the book is technically 2013, the website is current.
• ggplot2 documentation
• O'Reilly text.  Comprehensive book on R, not just for visualization, but chapters on viz also.
• Nice site for playing with R online.
• CodeAcademy for R. 
  
• The resources in R and ggplot are endless!  Datacamp, and many, many more.
• If you are interested in the statistical side of R, you may want this book as an R reference.

• For the Tableau module of the course, there are many sites and youtube videos.  Just touching the surface with some links used in the course:
• Resources:
• Tableau Public training videos (used for our labs.)  Tableau has not updated these for the 2020 version, but the 2019 version is almost identical.  The main difference is that the 2020 version is using "relationships" as a way of specifying joins and unions.  Our course videos have annotations and updates.
• Tableau provides many free training videos
• There are short training videos on the Tableau Desktop and Tableau Prep download pages.  You will have to sign in with your Tableau login/pwd to access.
• Tableau Desktop Getting Started Training Videos.
• Many of these videos have not been updated for 2020.  (The updates are not crucial.)
• They have a separate short video summarizing 2020 upgrades.
• And they have a page with links to individual videos for each upgrade
• One that you will probably want to look at is:  Relationships
• Tableau Prep Getting Started Training Videos 
• There are excellent training videos by Simplilearn.  The introductory videos shown are from 2018.  My annotated versions have some explanations relevant to  our course, and I have also updated them for 2020.  Simplilearn has a 2020 version of a  full 6-hour course on introducing Tableau; however, that is overkill for this course, and I would rather spend that time on learning some additional intermediate topics and other types of charts, which our course covers in later videos.
• SimpliLearn Tableau beginning tutorial, Part 1, and my annotated version.  (used for our labs) 
  
• SimpliLearn Tableau beginning tutorial, Part 2, and my annotated version.  (used for our labs)
• anything by Ryan Sleeper, including his excellent book,
  or, if you really want to invest in Tableau training,he has an elearning site (subscription) that is excellent.
• 50 tips in 50 minutes, by Jeffrey Schaffer
  
• 50 charts in 50 minutes
• Super Data Science links
• There are too many support sites, blogs and videos to mention.  Stackoverflow is one that deserves mention, but there are many others.
  

• Course Support:
• Assignment submission and grades will be maintained on Sakai.   

Software:

• We will be using R and RStudio for the R module of the course.
• Install R: http://www.r-project.org.   This is shown in detail in the Orientation module on Sakai.
• Install RStudio:  https://rstudio.com/products/rstudio/download/.  This is shown in detail in the Orientation module on Sakai.
• We will be using both Tableau Public and Tableau Desktop for the Tableau module of the course:
  
• Download Tableau Public
• Free student license for Tableau Desktop Professional bundled with Tableau Prep Builder and eLearning now.
• You will be sent links and product key information 
• Tableau provides many free training videos
• There are short training videos on the Tableau Desktop and Tableau Prep download pages.  You will have to sign in with your Tableau login/pwd to access.
• Tableau Desktop Getting Started Training Videos.
• Many of these videos have not been updated for 2020.  (The updates are not crucial.)
• They have a separate short video summarizing 2020 upgrades.
• And they have a page with links to individual videos for each upgrade
• One that you will probably want to look at is:  Relationships
• Tableau Prep Getting Started Training Videos 

Sakai:
As of this writing, Sakai will be used for course announcements, homework submissions, and grade postings.  While the raw scores posted on Sakai should be correct (although I have encountered some problems with that too!), please do not rely upon Sakai's Course Total calculations.  Usually, they are okay, but there have been problems.  I check the total grade postings periodically, to check up on Sakai's calculations.  Certainly, before the mid-term grade posting on Locus, and before the drop deadlines, check your grades (and I will too!)  Grades are calculated as specified in this syllabus. 

Class Format:
This class is completely online and it is asynchronous.  There are videos for lectures and "lab prep".  It is important to come prepared to any zoom meetings that we have, as I will not repeat entire lectures and labs during those meetings  However, students have found the videos to be a good substitute for in-person lectures, and in some ways better, as you can start, stop and repeat those segments as required.  There will be some zoom "Q & A" meetings, times to be determined by student poll.  There will be some mandatory project team meetings with me, and I will always be available for individual and team meetings to help you when you need help.

Cell Phones: Only you know the relative importance of any particular cell phone call, and whether it is important for you to answer a call immediately rather than later. I do want you to be respectful of your classmates and disrupt the class  as little as is practical. If you get cell phone calls with fair frequency, be sure to have the ring muted before coming to class. If you rarely get calls, you might not mute it ahead, and your cell phone may happen to ring. Get rid of the noise as soon as possible, and do not get flustered. I assume you will move outside the classroom for a conversation. If you get fairly frequent calls that you are likely to consider important answering, sit in a place where your exit and re-entrance are as unobtrusive as possible.

• Using or copying an outside person's work on an exam or assignment in any fashion. "Outside person" includes a person who put something on a web page. It has become depressingly familiar for me, most every semester, meting out penalties for using someone else's work on the web. Do not do it.
• Anything that vaguely resembles something from any Instructor's Manual anywhere.
• Work includes outlines, pseudocode, code, and documentation.
• Allowing your own work to be copied or used by an outside person.
• Submitting as your own work something that has been written by an outside person (or web site).
• Using any unauthorized reference on an exam or assignment
• Not acknowledging and describing in writing on an assignment any help you received or gave.
• If you are working on a pair or group project, an "outside person" only refers to people other than your assigned partner or team.
• Note that cheating goes both ways: both giving and receiving.
• Consultation is allowed with the TA (if we are fortunate enough to get one) and with me. If you consult with the TA and/or with me, still make a comment at the top of your work about the substance and depth of the help.

• The meaning of program or query specifications (not the plan for the solution or the actual solution).
• The tools used to write programs.
  
• The restrictions of the current programming language syntax.

Students with Disabilities:  If you have a documented disability and wish to discuss academic accommodations, please contact the Student Accessibility Center (773-508-3700 and SAC@luc.edu) as soon as possible.  Students with documented disabilities who provide me with a letter from the SAC office will be fully accommodated as per the terms of the letter. 

The dates below give the sequence and a general idea of the time spent, though we may get ahead or behind this time schedule at different points, depending on the needs of the class.  Be sure to keep up with where we really are in class.  There will be weekly updates on Sakai, reflecting what we actually cover (and therefore what is due, and when).

Except for the first lecture and the exam, every lecture is a lab.  You are expected to participate in all labs.  Some assignments are listed as "homework", but are actually started together in class, similarly to a "lab".  So the rule of thumb is:  You have to be in class for everything, and complete all assignments the way you are instructed to in class.