CSC 239 Personal Computing

Fall 2005

Instructor

Dr. Craig Miller
Office: 830 CTI Building, 312-362-5085
Email: cmiller@cs.depaul.edu
Office Hours: Announced on Web page

Course Meeting

Monday and Wednesday 3:10 - 4:40
CS&TC 228

Required Text

There is no text book for this course. Slide presentations, lab assignments, and class lecture and discussions will be used in place of a text.

Overview

The aim of the course is to illustrate simple statistical methods for data analysis. The course topics include descriptive statistics, an introduction to statistical inference (confidence intervals and hypothesis testing) and linear regression models.

During the course students will learn how to develop Excel workbooks for computing elementary statistics using the data analysis toolkit. A variety of statistical, mathematical, logical, and text functions in Excel as well as the Excel Chart and Data features will be presented.

Goals

At the end of this course, you will understand and be able to:

1. Perform simple data analyses using Excel and to interpret the output of your analyses
2. Be informed about and critical readers of quantitative arguments.
3. Create written reports including Excel tables and charts, summarizing the results of your study.

Scientific Inquiry Learning Goals

Courses in the Scientific Inquiry Domain are designed to provide students with an opportunity to learn the methods of modern science and its impact in understanding the world around us. Courses in this domain are designed to help students develop a more complete perspective about science and the scientific process, including:

1. An understanding of the major principles guiding modern scientific thought.
2. A comprehension of the varying approaches and aspects of science.
3. An appreciation of the connection among the sciences and the fundamental role of mathematics in practicing science.
4. An awareness of the roles and limitations of theories and models in interpreting, understanding, and predicting natural phenomena.
5. A realization of how these theories and models change or are supplanted as our knowledge increases.

Grade Determination

Grading is based on the manner in which you fulfill the objectives of this course. I will grade all your assignments on a percentage basis, which I will then convert to a letter. I will convert percentages to letters based on the following schedule:

Participation. The participation grade is based on your presence in class and your meaningful contributions to class discussions. If I know your name, you're probably doing well. If I don't, please participate more.

Homework. There will be six written assignments taken from the material in the course. Homework will be due approximately one week after it is assigned. Late assignments may be submitted 3 days late with a penalty of 20 percentage points. Additional assignments for extra credit will not be offered.

Midterm Project. The midterm project will summarize the learning in the first half of the course. The project will include a statistical analysis and a written explanation of the analysis.

Final Presentations. There will be no final exam for this course. Instead, we will use the final exam time (Friday November 19, 2:45 to 5:00) to present group projects. The projects will include a group grade which every project member will share. Further, each group member will be given the opportunity to state her own contributions to the project which, in addition to your part of the group presentation, will help decide an individual grade.

Students receiving more than 90% of possible points are guaranteed at least an A-, more than 80% at least a B-, more than 70% at least a C-, and more than 60% at least a D.

Policies

Attendance. I expect that you will attend every class; it is the single most important action you can take in mastering the course objectives. You are responsible for all material covered, assignments delivered or received, and announcements made in class sessions that you miss. In addition to the explicit 5% in the table above, I reserve the right to use class participation and attendance in resolving borderline grading decisions.

School policies on instructor evaluation, email, plagiarism and incompletes.

Tentative Schedule