Syllabus for Statistics 185
Professor: Mark McClure
Statistics vs data science
Check out Wikipedia's article on Data Science. Quoting from that article, I guess that
- Data science is "The Sexiest Job of the 21st Century" (Wikipedia cites the Harvard Business Review)
- There could be a global shortage of 1.5 million data scientists (Wikipedia cites McKinsey & Company)
Just what is this hot, new field?
- According to the same Wikipedia article, data science is a "concept to unify statistics, data analysis and their related methods" (Wikipedia cites a prominent text).
- According to page 8 of our textbook, "Statistics is the study of how best to collect, analyze, and draw conclusions from data".
- More blunlty, Nate Silver says that data science is "sexed-up term for statistics".
Statistics (or Data Science, if you prefer) is an applied field with a wide range of practial applications that is of growing importance in today's data driven world. In this course, you will:
- Learn the qualitative language of data: What are the basic structures, variables, summaries, and charts that we use to describe and understand data? What data can we find and how do we collect more?
- Learn how to analyze data quantitatively: What specific distribution should we use to model a specific data set? What do quantitative measures associated with a distribution tell us about the data set?
- Learn how to make inferences from the data: What conclusions can we draw from a given data set or collection of observations? And how confident can we be in those conclusions?
- Deal with large, real world data in all it's messiness: This is meant to be a practical class where you can develop some skills that help throughout your college career and beyond. As such, we'll learn how to use the computer to work with actual data.
- The Text: We will use the Open Intro statistics text. This is an open text made freely available through a Creative Commons license.
This class will meet mostly online. As such, a decent computer and reliable internet connection are essential. All required software is either open source, available via a UNCA site license, or will be accessed via the web - including:
- Zoom: For attending class remotely.
- MyOpenMath: We will have regular auto-graded homework using MyOpenMath. You can login there, using the information presented in class.
- Stat Talk: I've set up an online forum called Stat Talk where we can discuss all aspects of statistics. Not only is this a great place ask HW questions but participation is mandatory. You will earn points for certain assigned questions.
- Colab: A Google based tool based on Python for scientific computing and graphics. This is the tool that will allow us to work with large, real world data sets.
This course is listed as a "hybrid" course, giving us a lot of flexibility to set up the course in the best way to deal with Covid. The experience of the last few semesters indicates that the course lends itself to an online experience so it is my intention to run it mostly online. Here are the details of how that should work:
- Every class lecture and problem session will be delivered via Zoom. For at least the first half of the semester, that will be the only way that lecture is delivered.
- I am open to the possibility of some in class lectures during the second half of the semester, if COVID counts fall. Such lectures would still be available via Zoom to students who prefer it.
- Attendence (via Zoom) is mandatory. Most class periods will include a problem session in break out rooms which will affect your grade, as detailed below.
- Most assessment will be done via online homework and quizzes, as detailed below. There will be two exams during the term with in class portions - one during the week of March 1-5 and one during the week of April 19-23. The exam will be spread out so that only 1/3 of the class will be in the room during the exam.
- Homework: There will be two types of graded homework:
- MyOpenMath, which is online and automatically graded.
- Forum posts.
- Quizzes: We'll have fairly frequent quizzes, which will essentially be short but timed MyOpenMath sessions.
- Computer Labs: A major part of the class will involving using the computer to work with large data sets. Thus, we'll have several computer labs to help with this.
- Computer Labs: There will be two exams during the term, as described above.
- Participation: You will earn up to 60 points simply for attending regularly (in-person or online), asking questions, and participating in any in class labs or problem sessions.
- Final grades: I will determine final grades using a scale not more stringent than the standard 90-80-70-60 scale. You will be apprised of your standing as the term progresses.
- Late work: In general, I don't accept late work.
- Learning statistics: You don't have to be a mathematical genius to absorbs the fundamentals of statistics and learn how to apply statistics to real world problems. You do need to work fairly hard and consistently, however.
You are not undertaking this challenging task alone.
Here are a few sources of assistance:
- Me: I like to talk to people about math and stat! That's why I chose this profession. You can find me on Zoom most days between 9:30 and 10:30, as well as on our forum.
- Your classmates: Most people learn best by talking things through with others. You will find that you can both learn from and help your fellow classmates. In particular, if your classmate is explaining a fine point to you, then you are helping them!
- Our class forum: A kinda combination of the previous two that never sleeps!
- The Math Lab: The Math Lab has always rocked! It's now available for both in person and online tutoring, as detailed on their webpage.
Your rights and responsibilities
It's worth understanding your rights and responsibilities as a student at UNCA. One of my responsibilities is to make sure you have the information that you need to do that. Since this is common to all classes, I've got that information on this legalese document.