Course Syllabus: Stat 500 Section 2 Spring 2011
Instructor:
Dr. Mosuk Chow
Office: 315 Thomas
Phone: 863-8128 (e-mail: mchow@stat.psu.edu)
Office Hours: Tues , Wed 2:00-3:30pm
or by appointment
Grader information: (will be announced on the course ANGEL site)
Aim:
The course is an introduction to the basic concepts and methods of applied
statistics. It is intended for graduate students who have one undergraduate statistics
course (students without an undergraduate course in Statistics would need to have strong
math skills). It is suitable for students who wish to review the fundamentals before
taking additional 500 level Statistics courses.
Textbook: An Introduction to Statistical Methods and Data Analysis by R. Lyman Ott
and Michael Longnecker ( 6th edition) bundled with Minitab 14 student version.
International Thompson Publishing. ISBN: 9781111116318. Available at Penn State
bookstore. The textbook is on reserve in Physical and Math Science Library (PAMS) at
201 Davey Lab. Minitab is also available in the computer labs on campus. (5 th edition
of the textbook can be used.)
Grades:
Homeworks
20 % (submit to dropboxes on ANGEL site)
Midterms:
50 % (in class 6:00- 6:50pm on Feb 28 and March 28) location
will be announced
Project:
5 % ( project due April 27)
Final Exam:
25 % (your e-lion will show the date when decided by the system)
Grading (tentatively): Course grades in each of the nine categories will be tentatively
awarded based on the following lower bounds:
F
0
D
60
C
70
C+
77
B80
B
83
B+
87
A90
A
93
Exams: Midterm exams and final will be closed book and comprehensive. More focus
will be given to material not covered in the prior exams. For midterm exams, you will be
allowed to bring in a formula sheet made up by yourself. This sheet may comprise of a 2sided 8.5x11 inches sheets. For final exam, you can bring two 2-sided 8.5x11 inches
sheets. No early or late exams will be allowed without a legitimate excuse.
1
Home works: Homeworks are to be submitted to their respective dropboxes by the due
day. You must show all work on the homework problems to get full credit. Doing the
homework promptly and carefully is necessary for learning the material. A reasonable
amount of collaboration is allowed on homework. However, each student must turn in his
or her own written work which reflects his or her own individual understanding of the
material. Late home works will have 20% off for each day late. Note that the lowest
homework score will be dropped.
Solutions: Solutions for the homework assignments will be posted with a link to it from
the homepage of Stat500.
Project: You will be given a data set and you will be asked to employ techniques you
have learned throughout this course to analyze the data set. One final team project will be
assigned. Each team will consist of two to three students.
Discussion: On our ANGEL site, there are Discussion Forums. You can post questions
on course materials, homeworks, etc. All of you are encouraged to answer the questions
or to make comments.
Academic Integrity: All Penn State and Eberly College of Science policies regarding
academic integrity apply to this course. See
http://www.science.psu.edu/academic/Integrity/index.html
ECOS Code of Mutual Respect: The Eberly College of Science Code of Mutual
Respect and Cooperation ( visit http://www.science.psu.edu/climate/code-of-mutualrespect-and-cooperation-1 ) embodies the values that we hope our faculty, staff, and
students possess and will endorse to make the Eberly College of Science a place where
every individual feels respected and valued, as well as challenged and rewarded.
ECOS advising: The Eberly College of Science is committed to the academic success of
students enrolled in the College's courses and undergraduate programs. When in need of
help, students can utilize various College- and University- wide resources for learning
assistance. http://www.science.psu.edu/advising/success/
Course Objectives
Upon completion of this course you will:




Appreciate and understand the role of statistics in your field.
Develop an ability to apply appropriate statistical methods to summarize and
analyze data for some of the more routine experimental settings.
Make sense of data and be able to report the results in appropriate table or
statistical terms for inclusion in your thesis or paper.
Interpret results from various computer packages (Minitab, SPSS, SAS) and be
able to use Minitab to perform appropriate statistical techniques.
2
Getting Started
Time frame: January 10, 2011 - January 15, 2011
Assignments:


Complete the steps outlined in the Welcome Letter from
your instructor (sent to you by Student Services with
other course introductory materials) to acquaint yourself
with the course environment.
Complete the activities in the Getting Started folder (see
the Lessons tab) by Jan 15
Lesson 1: An overview of Statistics, gathering data and graphical methods,
introduction to Minitab
Time frame: January 10, 2011 - January 19, 2011
Assignments:

Work on Homework 1 (due January 19)
Lesson 2: Summarizing data: measures of central tendency and measures
of variability, box plot
Time frame: January 19, 2011 - January 26, 2011
Assignments:

Work on Homework 2 (due January 26)
Lesson 3: Probabilities, conditional probability and independence, types of
variables and probability distributions
Time frame: January 26, 2011 - February 2, 2011
Assignments:

Work on Homework 3 (due February 2)
3
Lesson 4: Binomial distribution and normal distribution
Time frame: February 2, 2011 - February 9, 2011
Assignments:

Work on Homework 4 (due February 9)
Lesson 5: Sampling distribution and central limit theorem
Time frame: February 9, 2011 - February 16, 2011
Assignments:

Work on Homework 5 (due February 16)
Lesson 6: Introduction to inferences, confidence interval for population
proportion, margin of error and sample size computation
Time frame: February 16, 2011 - February 23, 2011
Assignments:

Work on Homework 6 (due February 23)
Midterm 1
Time frame: 6:00 - 6:50 pm, Feb 28, 2011

location will be announced.
Lesson 7: Confidence interval for population mean when population
standard deviation is unknown, t-distribution, choosing the sample size for
estimating the population mean
Time frame: February 23, 2011 - March 2, 2011
Assignments:

Work on Homework 7 (due March 2)
4
Lesson 8: Hypothesis testing, type I and type II error, statistical test for
population proportion, p-value approach to hypothesis testing
Time frame: March 2, 2011 - March 16, 2011
Assignments:

Work on Homework 8 (due March 16)
Lesson 9: Statistical test for using rejection region approach, statistical test
for population mean, how to use confidence interval to draw conclusion
about two sided test, power and sample sizes
Time frame: March 16, - March 23, 2011
Assignments:

Work on Homework 9 (due March 23)
Midterm 2
Time frame: 6:00 - 6:50 pm, March 28, 2011

location will be announced
Lesson 10: Comparing two population means, independent samples versus
paired data, two sample t-test, paired t-test
Time frame: March 23 - April 6, 2011
Assignments:

Work on Homework 10 (due April 6)
Project (posted April 1)
Time frame: April 1 - April 27, 2011
Assignments:

Due April 27
5
Lesson 11: Comparing two population proportions, contingency table and Chisquare test of independence, comparing two population variances
Time frame: April 6, 2011 - April 13, 2011
Assignments:

Work on Homework 11 (due April 13)
Lesson 12: Simple linear regression, correlation, inferences for simple
linear regression
Time frame: April 13, 2011 - April 20, 2011
Assignments:

Work on - Homework 12 (due April 20)
Lesson 13: Multiple regression, one-way ANOVA and two-way ANOVA
[Note: The details in Lesson 13 will not be required for the final exam.]
Time frame: April 20, 2011 - April 27, 2011
Assignments:

Work on - Homework 13 (no need to submit)
Lesson 14 - Summary: To determine what statistical methods to use for
specific situations, summary and review
Time frame: April 20, 2011 - April 30, 2011
Assignments:



Review material learned in STAT 500
Work on "to choose statistical techniques"
Project - due April 27
6
The instructor will offer bonus points if you find mistakes in any of the course content
dealing with statistical calculation. These bonus points will improve your grade in
marginal cases.
7