CSC 324 Data Analysis and Statistical Software II
Summary
The course topics include:
- Inference for distributions: inference for a population mean, comparing two population means using paired or independent samples, checking normal assumptions.
- Multiple regression and correlation, analysis of residuals.
- Logistic regression
See extensive course description at the course website.
The objectives of this course are to:
- teach students to perform simple data analyses using SAS and to interpret the output of their analysis;
- enable students to be informed and critical readers of quantitative arguments,
- appreciate the role of statistics in empirical research and scientific study, and
- gain flexible problem-solving skills applicable to unfamiliar statistical settings.
Texts
REQUIRED
A Second Course in Statistics: Regression Analysis, 7th ed., William Mendenhall, Terry L. Sincich, Prentice Hall, 2011 (ISBN: 0321691695) - Or previous edition
Introductory notes on SAS will be posted on the course website.
OPTIONAL:
Optional text for SAS: Applied Statistics and the SAS Programming Language, 5th edition, by Cody, R.P. and Smith. J.S. Prentice Hall (2005), ISBN: 0131465325.
Grading
Homework assignments (40%).
Exam (30%). Tentatively scheduled on Wednesday May 29th, 2013 (week 9).
Final Group Project. Details will be provided in class. (30%)
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.
Prerequisites
IT223 or consent of instructor. Students should be familiar with statistical inference methods, including sampling distributions, confidence intervals and hypothesis testing. A brief review of these topics will be covered in the first lecture of the course.
Software
Students have the option of using either SAS or R.
The statistical package SAS9.2 is available in all DePaul labs. Two lab sessions (to be recorded for online students) will be scheduled during the quarter.
The statistical software R is free. Installation instructions are posted on the course website.
A review of basic concepts relevant to our course, students should have already covered much of this material elsewhere. Inference for the mean of a population. Introduction to SAS and R. (Chapter 1: sections 1.1 through 1.9)
Inference on two population means: two independent samples and paired samples. Lab session. (Chapter 1: Sections 1.10-1.11.)
Linear regression & correlation. (Ch. 3)
Multiple regression models: estimating model parameters and understanding the model assumptions. (Chapter 4: sections 4.1 through 4.7, 4.14)
Multiple regression: residual analysis and model diagnostics (Chapters 7 and 8 (excluding 8.6))
Model selection methods (Chapter 6)
Building more complex models: non-linear regression, polynomial regression. (Section 4.9, 4.10, 4.11, 4.12, 4.14. Chapter 5. )
Logistic regression and predictive models for qualitative variables (Chapter 9: sections 9.5,9.6)
Exam
More complex models, and advanced topics in regression
This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.
Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course
content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The
evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely
separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation.
Students complete the evaluation online in CampusConnect.
This course will be subject to the university's academic integrity policy. More information can be found at http://academicintegrity.depaul.edu/ If you
have any questions be sure to consult with your professor.
All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.
All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at http://www.cdm.depaul.edu/Current%20Students/Pages/PoliciesandProcedures.aspx.
Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that
you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296