Instructor: Dr. Julie M. Clark jclark@hollins.edu

Office: Dana 107                           Office Phone: -6524

Office Hours: Posted here and on my office door. Additional hours available by appointment and by chance.

Course Schedule: MWF, 10:10-11:20 AM                            Location: DANA 111

Course Web Site: http://moodle.hollins.edu/mod/url/view.php?id=69
Please check the course web page frequently for updates in the schedule, handouts, and other comments or important information.

Pre-requisite: q and appropriate score on the mathematics placement test, or permission of instructor.

Required materials:

Text: Investigating Statistical Concepts, Applications & Methods, 3rd Edition, by Beth L. Chance & Allan J. Rossman. You need to purchase a copy of the text from here. You may purchase a pdf copy for $5.00 or a printed copy for $20.00.  (Please purchase the combined, 3rd edition version that contains both Minitab and R instructions, and be sure to enter “Hollins University” in the Company Name slot.)  Note that there have been updates and corrections since last Fall, so please don’t try to use someone else’s copy from last year.

You will also need a Hollins email address, a three-ring binder, and you will probably want a scientific calculator. Handouts will frequently be provided, and you are responsible for receiving and keeping these materials. You will also be expected to read and work through the class notes and Investigations during and after each class.  We will make frequent use of the statistical analysis packages RStudio & Minitab (version 18), which are very widely used in business and industry, as well as in educational settings. We will also frequently be using Java applets that run on both Mac and PC. No prior knowledge of these software tools is assumed; you will receive detailed instructions regarding their use when the need arises. RStudio, Minitab and the applets are available through the Hollins network (we will run R-Studio from the Hollins R server: http://rstudio.hollinsnt.hollins.edu:8787/ )  . You may also obtain personal copies of both RStudio and Minitab if you like (instructions will be provided in class when we get to that point). You are also encouraged to use a scientific calculator as necessary.

Overview:

Statistics is both an exciting intellectual discipline and a powerful scientific tool. It is a mathematical science in the sense that it makes use of mathematics extensively, but it is not a branch of mathematics. Since statistical thinking abounds in everyday life and statistical methods are used in most academic disciplines; the ability to reason with data is essential to a liberal education. Since statistics involves a variety of interesting applications of mathematics, it is particularly appropriate for mathematics majors to study. Moreover, statistics is an especially important field of study for those planning to undertake graduate study or to pursue careers in education, computer science, economics, business, law, science, and medicine.

Statistics may be defined as the science of reasoning from data; it is therefore concerned with all aspects of data analysis, from the collection of data to the summary and display of data to the construction of models that represent the data to the drawing of conclusions from data. This course will introduce you to all of these facets by exposing you to practical applications involving genuine data. Since the practice of statistics demands the use of computers for analyzing data, you will use the computer fairly extensively in this course. You will also be expected to effectively communicate your understanding and interpretation of these aspects of data analysis. Some of the key ideas to be studied in this course include data collection strategies and their scopes of conclusion, the role of randomness in collecting data and drawing conclusions, graphical and numerical summaries of data, assessing statistical significance, and estimating with confidence.

Goals:

My overarching goal for this course is to help you to develop basic strategies and skills for analyzing quantitative data. My hope is that you will then be able to adapt and apply these intellectual habits to a variety of circumstances in your academic, professional, and even personal lives. By the conclusion of the course I hope that you have improved your ability to:

  • apply and interpret the results of a variety of statistical techniques including both descriptive and inferential methods;
  • understand many of the fundamental ideas of statistics, such as variability, distribution, association, causation, sampling, experimentation, confidence and significance;
  • analyze and assess statistical arguments such as those found in the popular press as well as in scholarly publications;
  • use statistical software to both analyze data and to explore statistical ideas; and
  • communicate your knowledge of statistical ideas effectively.

Classroom Culture:

I believe that understanding results from investigation and discovery, not from passive observation. So, as opposed to merely passively taking notes while I lecture, you will spend most of your class time actively engaged with the material. Each day you will work through Investigations carefully designed to lead you to discover and explore statistical ideas and techniques. Please come to class prepared through whatever readings and problems that I assign, and please be willing (eager!) to work during class time and to collaborate with your classmates and to ask questions of me. This will not only help you learn the material and perform well in the course, but will also produce a much more enjoyable learning environment for all of us. Class attendance is essential, as the in-class activities should prove to be valuable learning experiences. Needless to say, you are responsible for everything presented in class.

I also expect you to devote substantial outside-of-class time to you work for this course, typically 8-12 hours per week. I anticipate that this work will be divided among finishing Investigations, reviewing your class notes, working on homework assignments and practice problems, working on Q projects, and preparing for tests.

We will make fairly extensive use of software and applets in this course. They will prove useful in at least three ways:

  • for performing calculations and creating graphics necessary for analyzing data;
  • for conducting simulations to approximate long-run behavior of random phenomena, and
  • for addressing “what if” questions that allow you to explore statistical concepts.

Minitab data files and Java applets are available on the web here.

Evaluation:

In order to give you a variety of opportunities to demonstrate your learning, your course grade will be determined by the following components, with relative weights as indicated:

Practice problems (daily)/ Participation: 13%
Homework Assignments: 25%
Tests: 25%
Q Projects: 15%
Final Exam: 22%

You cannot pass the course unless you submit the final exam.

Practice problems/Participation

There will almost always be a practice problem for you to complete between each class. These will be informal checks on your understanding of the new material. We will go over these in detail in class the next day. Practice problems should be submitted through Moodle no later than 8:00 AM before class. Each submission will be scored on a scaled of 0-2 (0 for no attempt, 1 for a half-hearted attempt, and 2 for a reasonable attempt). The practice problems will not be scored on correctness although you will receive feedback through Moodle.  Observe that merely submitting the practice problems and attending class make up 13% of your final grade in this course.  That is more than 1 letter grade!  So it would be foolish to fail to submit any practice problem.

You will frequently be asked to complete a brief data collection survey for use in later analysis. Timely submission will count toward your participation grade.

Regular class attendance is an indication of your interest in, and commitment to this course. You are expected to attend class every day, to participate in class discussions and activities, and to ask relevant questions. Part of your final course average will be based on your attendance and participation. Attendance will be taken at the beginning of class each day, and a late arrival will count as an absence. If you do miss a class for any reason, you are expected to make-up the missed work (and submit your practice problem on time) before the next class. Failure to do so will lower your participation grade. Any student that misses more than 1/3 of the total classes will automatically fail the course.

Homework Assignments:

You will have frequent homework assignments – typically once a week. Such assignments are due by midnight on the assigned day. Late assignments might be given feedback, but will not be given a grade. If you submit all the homework assignments, I will drop your lowest homework grade.

You will have a test after Chapter 1 one and another after Chapter 3, and a comprehensive final exam. The tests may have both an in-class and take-home portion, or they may be strictly in-class. The dates for these tests will be announced at least one week in advance. The final exam will be an open-book, take-home exam, distributed on the last day of classes.

Q Projects:

Stat 251 is a Q course, meaning that once you have successfully completed the course, you will have satisfied the Q component of Hollins’ general education requirements. You will be assigned at least one Q project which involve your analyzing and drawing conclusions from data that you find and collect yourself. The first project is based on Chapter 1. You will submit these projects as part of a team of students.  Specific instructions for the projects will be made available when we get to that point in the course.

Portfolio Assignments:

All Hollins mathematics majors and minors are required to accumulate a mathematics portfolio throughout their careers at Hollins. The portfolio should demonstrate a student’s mathematical growth and experiences at Hollins. Students must keep copies of all assignments that are designated “portfolio assignments” in any given mathematics/statistics course. Students are strongly encouraged to keep copies of all their work in Stat 251 for possible inclusion in the portfolio. The Q projects and any two homework assignments of your choice will be the portfolio assignments in Stat 251.

What I expect from Students:

  • Ask questions early and often if there is something you do not understand about the material or course structure. Even if your question is “huh?”, it needs to be asked as soon as possible.
  • Be interested and committed to the course. Attend class and KEEP UP.
  • Be courteous of the instructor and your fellow students. This includes no cell phones or web surfing in class, completing and submitting assignments on time, etc.

What Students Should Expect from Me:

  • That I’ll be courteous and respectful of students, including learning your names, treating you professionally, and beginning and ending class on time.
  • That I’ll carefully prepare the course materials, including responding to your feedback and questions.
  • That I’ll provide prompt and informative feedback on your work and will keep you informed of how I am evaluating your performance.

Need help?

Please feel free to come by my office, send me an email, catch me on-line, or call me at home anytime. In addition to my posted office hours, you may also email for an appointment.

Disclaimer:
I am not really anywhere near as organized as this lengthy syllabus might suggest. All of these details are subject to change as the course develops. I welcome and value your input.