CSC 423 Data Analysis and Regression

Steve Jost

Office: CDM 744
Summer II 2016-2017
Class number: 41933
Section number: 501
MW 5:45PM - 9:00PM
CDM 00226 Loop Campus


CSC 423 is a course on multiple regression modeling and other statistical methods. Course learning goals include:

  • teach students to perform data analyses using statistical software,
  • enable students to be informed and critical readers of quantitative arguments,
  • understand the role of statistics in scientific and business applications,
  • gain flexible statistical problem-solving skills applicable to a variety of settings.


Mendenhall and Sincich, Second Course in Regression Analysis, 7th Edition, Prentice Hall/Pearson, 2012.


Grading Scale: 94-100: A; 89-93: A-: 85-88: B+; 80-84: B; 75-79: B-; 70-74: C+; 65-69: C; 60-64: C-; 55-59: D+; 50-54: D; 0-49: F.
Grading Breakdown: Homework Projects: 40; Group Final Project: 30; In-class Final Exam: 30.
Late penalties for projects: The late penalties are: up to one week late: 10%, one to two weeks late: 30%, two to three weeks late: 70%, three or more weeks late: 100%. A 15% resubmit penalty will be assessed for resubmitted assignments. Resubmitted assignments are also subject to the above late penalties.


IT 403 or another first statistics course.

Other Regulations

Class registration is not allowed after the first week of class.
Students must keep backup copies of all submitted assignments.
Extra credit assignments are not given.
No late assignments will be accepted after final grades are submitted to the registrar.
An incomplete is hard to get in CDM. It is only allowed for a major illness (typically requiring hospitalization) or a death in the family. To receive an incomplete, you must be passing the course before the incident that makes the incomplete necessary occurs. In any case documentation is required, and more than one half of the work must be completed for the course.
Students should carefully check project submissions before submitting them. Submitting a wrong version or otherwise incorrect assignment is not a valid reason to waive the late penalty.
If you have trouble submitting any project, email the completed project to the professor to show that that it was completed on time.
If a student must reschedule an exam, the professor must be contacted before the date of the exam. A late penalty will be assessed for students that miss an exam without contacting the professor beforehand.

Day 1: Course overview and prereqs, univariate descriptive statistics, exploratory data analysis. Introduction to SAS and R. Sections 1.1-1.9.

Day 2: Review of z- and t-tests. Two sample tests. LAB: SAS and R for univariate data analysis. Sections 1.9-1.11. Chapter 2.
Day 3: Correlation, simple linear regression, goodness-of-fit tests, residual analysis. Chapters 3, Sections 8.1 to 8.5.
Day 4: Multiple regression, backward selection, dummy variables. Intro to ANOVA. Sections 4.1 to 4.9. Sections 5.7, 5.8
Day 5: Polynomial regression models, interactions, influence points, multicolinarity, test for autocorrelation. Sections 4.10 to 4.14, Chapter 5, Sections 8.6, 8.7, 7.4.
Day 6: Model building, model selection algorithms. Variable transformations. Chapter 5, Section 7.6.
Day 7: Categorical Data Analysis, log-linear models, logistic regression, generalized linear models. Practice problems for final exam. Section 9.6.
Section 9.6.
Day 9: More about logistic regression. More about ANOVA. Case Studies. Discuss and answer questions about final projects. Sections 9.5, 9.6, Chapter 12.
Day 10: Present group final projects.

School policies:

Changes to Syllabus

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.

Online Course Evaluations

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.

Academic Integrity and Plagiarism

This course will be subject to the university's academic integrity policy. More information can be found at 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.

Academic Policies

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

Students with Disabilities

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