STAT 586 Interpretation of Data (I)

Fall 2008, Wed 6:40 - 9:30pm
SEC Building, Room 208, Bucsh Campus

Instructor: Minge Xie
Office Hours: Wed 1:30pm -2:30pm or by appointment
Office: Hill Center 565, Busch Campus
Phone: 732 445-2546 email: mxieATrci.rutgers.edu

TA: Mr.Wenqian Qiao
Office hours: Monday 3:00pm-5:00pm or by appointment
Office: Hill Center551, Busch Campus
Phone: 732-445-2617 email: wenqianATeden.rutgers.edu

Office Hours for the Final Week

Minge Xie:  Dec. 10 (Wednesday) 1:30 – 4:00pm (regular/additional)

Dec. 10(Wednesday) 9:00-10:30pm (additional)

Wenqian Qiao (TA):  Dec. 5 (Friday) 1:00-3:00pm (additional);

Dec. 8 (Monday) 3:00-5:00pm (regular);

Dec. 11(Thursday) 1:00-3:00pm (additional)

An Alternative Due Date of the Final Project

The final report is still scheduled to due on Dec.12 before the final exam. But for those who need a little extra time, you can hand in your final projects (slide into my office, Hill Center 565) by midnight on December 17^th, 2008.

Prerequisite: Level IV statistics. Recommended 16:960:563, 16:960:583.

Methods of modern data analysis with emphasis on statistical computing. Topics include univariate statistics, data visualization, linear models, generalized linear models (GLM), multivariate analysis and clustering method, tree method, and robust statistics etc. Expect to use statistical software packages, such as SAS (or SPS S) and Splus (or R) in data analysis.

Course Syllabus:

· pdf version

Homework Assignments:

· Homework No.1

o Example solution (key points) to R assignments

o Example solution (key points) to Splus assignments

o Example solution (key points) to SAS assignments

· Homework No.2

o Example solution (key points) to R/Splus assignments

o Example solution (key points) to SAS assignments

· Homework No.3

Handout Examples:

         R notes:

· notes.R.1

· notes.R.2

· notes.R.3

Splus notes:

· notes.splus.1

· notes.splus.2

· notes.splus.3

        SAS notes:

· notes.sas.1

· notes.sas.2 and notes.sas.2a (Box-Cox transformation) (or, note s.sas.2a old SAS macro Box-Cox transformation)

· notes.sas.3

Reading materials/ notes:

· Bootstrap method

· Regression Overview(Figure1.1;Figure1.1b;Figure1.2a;Figure1.2)

· GLM overview (Figure2.1, Figure2.2, Figure2.3, Figure2.4, Figure2.5, Figure2.6, Figure2.7, Figure2.8 )

· Extra* GLM notes No1 (Figure3.1, Figure3.2, Figure3.3, Figure2.4)

· Extra* GLM notes No2: (Table1, Table2)  ---

a. Computer codes (Example5.1 (sas), Example.2 (R/S+),Example2a (sas)), Example3 (sas))

b. DataSets (Example5.1 Data, Example.2 Data)

c. SAS micro halfnorm from M. Friendly's webpage

* These extra GLM notes may cover some topics that are not discussed in class. These notes are for students who like challenges and want to read more materials about GLMs.

Final Project:

  In the final project assignment, you are required to analyze one of your own data sets (if you identify one. Also, please let me know before hand) or the following data set (Dr. Hoover’s Class survey Data). Different from the homework assignmentss, you need to (1) form your own questions, (2) try and select statistical methodologies that are appropriate for the particular data, (3) document your analysis and write a report  (including introduction/description of the data, the questions of interest(aims, hypotheses, etc), models/methods used, analysis results, and final conclusions).  The final report is due on Dec.12 before the final exam, and it should not be longer than five pages (not including computing results/output).

Final Exam:

The final exam is on Dec.12 from 6:00-9:00pm. This is a close book exam, but you can bring with you up to two pages of "cheating sheets". Also please bring with you a calculator. Laptop computers are not allowed.

· click here for an example problem on the exam

Note: Link to the R software (free) http://www.r-project.org/
      Link to Rutgers Site Licenses page https://software.rutgers.edu/
      Link to e-academy.com  http://elms03.e-academy.com/splus/
      Link to stat 390 (intro to SAS) here