Web Page: http:// www.stat.psu.edu/~naomi/stat511/

 office hours, homework and exam solutions, practice exams, exam times, homework hints and corrections, etc. will be posted here

Texts:

Required:  Applied Linear Statistical Models, 5th Edition   Kutner, Nachtsheim, Neter and Li 2005 Irwin, Inc.  (Note: This is a real improvement on the 4^th edition, but you can use the 4^th if you prefer.  I will make sure that I have page numbers for both for readings and homework.)

Auditors

Auditors are encouraged to participate fully in lectures but may not attend Lab sessions or turn in material for grading.

Homework

Weekly assignments are designed to help you assimilate and practice the techniques covered in class and to prepare you for the material to come.  Some small assignments may be given in any class.  These are to prepare you for class and are due as you come into class.  1 point will be given for turning each of these in on time.  Longer assignments are due at the start of Friday’s lecture (for the bonus point) but may be turned in as late as Friday at 2:30.  (They can be placed in my mailbox.)

Homework, data and sample SAS commands will be posted to the Web.  Homework should be typed.  SAS output should be downloaded to a word processor and edited appropriately.  Equations and other mathematical notation can be added by hand as needed.

Students are encouraged to discuss homework, but the work you hand in must be your own.   Copying will be penalized.

Late assignments will be allowed only with the permission from Prof. Altman, documented by a note or e-mail.  Permission will be granted only in cases of medical or family emergencies, or conflicting university commitments.  If in doubt - ask.

Project

Students will work in groups of 2 or 3 on a data analysis project to answer a question of interest which requires several predictors.  E.g. Is gender a significant predictor of faculty salary, after accounting for years in rank and publication record?  Can freshman performance be predicted by SAT and high school scores at admission.  More details will follow.

Exams (exact times will be posted)

Mid-term 1: Week of Oct. 11

Mid-term 2: Week of Nov. 15

Final: Finals Week

Make-up exams, if necessary, will follow the scheduled exams.  Prof. Altman must be informed in writing of exam conflicts at least 1 week in advance.  Medical and family emergencies will be handled on a case by case basis.  Please do not come to an exam if you are sick - you may infect the rest of us, and I cannot allow you to take the make-up exam if you have already taken the exam. 

Regrades

Grading errors on homeworks should be brought to the attention of your TA within 2 weeks of the date on which it was returned.  Your failure to pick up your homework does not extend this deadline, unless the cause was a lengthy medical or family emergency, in which case you need to contact Prof. Altman.

Grading errors on exams should be noted in writing.  The exam paper and explanation of regrade should be given to Prof. Altman within 2 weeks of the date on which it was returned.

Homework and exam solutions will be available on the Web.  Homework solutions will usually be posted the Monday after the homework is turned in.

Grade Breakdown

homework                                     20%

project                                          15%

mid-term 1                                    20%

mid-term 2                                    20%

final exam                                      25%

Computing

SAS PC will be the official package used in the course.  Students may use Splus/R.  However, SAS output will be used on exams and in class. 

Syllabus

A detailed list of topics and readings is posted weekly to the course web page under "Readings".

Academic Integrity

Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students.

 What You Should Know to Succeed in Stat 511

Matrix Notation:

1.      Be familiar with matrix notation.

2.      Be familiar with use of matrix notation to summarize linear equations.

3.      Know how to form the inner product of vectors.

4.      Know how to multiply two matrices.

5.      Know how to multiply a matrix or vector times a scalar.

6.      Be familiar with matrix inverse.

7.      When does a matrix have an inverse?

Univariate Statistics

1.      Distribution (especially Normal, t and F).

2.      Use of tables for the Normal, t and F distributions.

3.      Normal probability plot to assess normality.

4.      Population mean and variance.

5.      Sample mean and variance and how to compute them.

6.      The one-sample t-test and confidence interval for the mean.

7.      The two-sample t-tests (including paired) and confidence intervals for the difference in means.

Regression

1.      Correlation - sample and population.

2.      Regression equation.

3.      Linear function.

4.      The ordinary linear regression model.

5.      Formulas for estimating the sample intercept and slope in ordinary linear regression.

6.      The ANOVA table for regression.

7.      R².

8.      The F and t-tests for the statistical significance of the regression relationship.

9.      T-tests and confidence intervals for the population intercept and slope.

10.  Confidence intervals for the regression line.

11.  Prediction intervals.

12.  Checking the residuals for curvature, constant variance, outliers and normality.

13.  Transformations of  X and/or Y to satisfy regression assumptions.

ANOVA

1.      One-way and two-way ANOVA models.

2.      ANOVA table.

3.      Checking model assumptions.

4.      F-tests for treatments and factors.