Syllabus for Statistics 225

Professor: Mark McClure

Course purpose

Statistics 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 the theoretical foundations: Statistics is built on probability theory. We'll learn the basics of probability theory and how to formulate computations in terms of integrals.
• 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

Materials

• The Text: We will be following the text Probability and Statistics for Engineering and the Sciences by Jay Devore. The bookstore has the 9th edition but I think that an earlier edition should work fine as well.
• Technology: There are several technological tools that we'll use including:
  • Anaconda: A distribution of the Python programming language with lots of tools for statistical computing and graphics. This is the tool that will allow us to work with large, real world data sets. Anaconda is installed on computers across campus and you can get your own copy for free from Anaconda's download page. We'll have several micro-labs this term that will require the use of Anaconda.
  • Math & Stat HW Discuss: There's a website where UNCA students and staff can talk about their homework in mathematics and statistics: Math & Stat HW Discuss. Not only is this a great place ask HW questions but participation is mandatory. You will earn points for certain assigned questions.
  • Online homework: We will have regular auto-graded homework using WebWork.

Grades

• Mid-term exams: There will be three exams during the term worth about 100 points apiece. Likely dates for the exams are:
  • Wednesday, September 19
  • Wednesday, October 24 and
  • Monday, November 19.
  Note that third exam is the Monday before Thanksgiving.
• Final exam: There will a comprehensive final exam on Monday, December 10 at 8:00 AM.
• Quizzes: There will frequently be short quizzes on Fridays. Each quiz could be worth anywhere from 10 to 30 points.
• Homework: There will be two types of homework:
  • WebWork, which is online and automatically graded.
  • Textbook assignments, which will not be collected but offer important practice.
  These homeworks will be posted as the term progresses.
• Computer labs: We will have a few micro-labs worth 5-20 points apiece. These will often be turned in via Math & Stat HW Discuss:
• Math & Stat HW Discuss: Participation in the online discussion forum, Math & Stat HW Discuss, is mandatory. In addition to the assignments we have there, you can earn:
  • Five points for a question that I like and
  • Ten points for an answer that I like to a non-assigned question.
• In class problems: We will frequently work problem sheets together in class. Quiz and exam problems will be closely related to these sheets. In addition, you will receive a 40 point class participation grade simply for participating regularly.
• 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.
• Cheating: I don't deal with cheating. If I suspect cheating strongly enough, I simply refer you to the provost and fail you for the class.

Advice

• 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.
• The typical day: Class is 1 hour and 15 minutes long and will often be divided between lecture and problem sessions. On Fridays, we will often have an assessment, either a quiz or an exam.
• Help: 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 stats! That's why I chose this profession. My office hours are posted on my webpage but I'm often around at other times as well. Please feel free to approach me any time you have questions.
  • 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!
  • Math & Stat Discuss: As already mentioned, there's a website where UNCA students and staff can talk about their homework in mathematics and statistics:
    Math & Stat HW Discuss
    It's actually my personal project so I frequent it a lot.
  • The Math Lab: We all know the Math Lab rocks! It's open long hours and is located right across the hall from my office. You will be welcome there and will definitely find people to talk to about statistics, as well as mathematics.

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.