Spring 2015, Prof. D. Cline  (Section 502)

Welcome to my Statistics 212 home page!  (The information below is tentative and some details may change.  Please check again later.)

STAT 212 is an introduction to standard statistical methods such as multiple linear regression, experimental design and the analysis of variance, and categorical data analysis.  Advanced methods that also may be discussed include general linear models, nonparametric density estimation, nonlinear and nonparametric regression, logistic regression, and inference for percentiles.

The prerequisite is STAT 211 or its equivalent (calculus-based introduction to statistics) and is required.

For comments or questions, e-mail me (dcline@stat.tamu.edu) or contact the TAMU Statistics Department.


PDF file of this Syllabus (tentative, check again later)

Course Information subject to change

Time and Place: MWF 1:50pm–2:40pm, Blocker 169.
Instructor: Prof. Daren Cline, Blocker 459D, 845-1443.
e-mail: dcline@stat.tamu.edu
Office Hours: MWF 10:00am–11:00am or by appointment.  (my schedule)
Prerequisite: Statistics 211 or equivalent (calculus-based introduction to statistics).
Grader: Sha Ni,  email: sn907@stat.tamu.edu.
Office hours: Tues 10:00am–11:00am, Thurs 12:00pm–1:00pm, Blocker 405A or 405F.  You may contact the grader for help on homework or questions on graded homework.  The grader will not accept late homework under any circumstances.
Requests for late homework (with valid university excuses) and questions about the exams should be made directly to me.
Help Sessions: TBA.  Statistics graduate student TAs (not just your grader) will be available to help you.
The laptops in the room are for statistics class use only.
Course Objectives: The purpose of statistics is to provide defensible analyses of experimental data. In this class you will be expected to
  • Understand models relating a response variable to one or more other variables.
  • Know the basic forms of experimental design and their purposes.
  • Know the correct statistical analyses, their purposes and limitations, what to conclude and what not to conclude.
  • Use a statistical application to analyze data.
  • Understand what makes a conclusion defensible.
  • Understand assumptions and how to check them.
Online Resource: eCampus  (See below for more details.)
Textbook: J. L. Devore, Probability and Statistics for Engineering and the Sciences, 8th ed., Duxbury.
Notes and Handouts: You are expected to download lecture notes and other handouts as they become available on eCampus, and to bring them to class.  The handouts include output from statistical computing packages with some explanation about how they were obtained.
Discussion Board: An online discussion board (in eCampus), monitored by the grader and myself, will be available.  I will originate topics as I see fit or by request; you may start threads within topics.  Its purpose is to allow you to converse freely with others in the class about the course, especially for homework.  I only ask that you give each other help in the form of hints and suggestions, but not complete solutions.  Courtesy and discretion are of course required.
The discussion board will be off-limits on exam days.
Computing: I will provide examples using JMP and other statistical software, which you may refer to for doing homework (recommended).  JMP will be made available to you for free (for your own computer) after the start of the semester.  The computers in the Open Access Labs have JMP also. 
Prerequisite: Statistics 211 or equivalent (calculus-based introduction to statistics).
Disabilities Help: The Americans with Disabilities Act ensures that students with disabilities have reasonable accommodation in their learning environment.  If you have a disability and need help, please contact me and Disability Services in B118 Cain Hall, 845-1637.
Academic Integrity: You are expected to follow the Aggie Honor Code and maintain the highest integrity in your work for this class.  This includes not passing off anyone else's work as your own, even with their permission.  Please see the homework and exam policies below for specifics.
Copyright: All the resources I provide for this course are copyrighted and may not be copied, sold or distributed without my express, written permission.

Grading

Homework: Homework is worth 20% of the term score.  None may be dropped.  It will be assigned online and collected regularly.  Late homework will not be accepted without an approved excuse.
Method and communication are as important in this course as are final solutions.  Homework is to be detailed and clear, with all steps provided, on 8½×11 paper and stapled in the upper left corner.  Computer output should be pasted into solutions as needed.  (Do not append it to the end of your homework.)
Please see the homework policy below.
Exams: There will be two midterm exams worth 22.5% each and a final exam worth 35%.  All exams are cumulative and closed book.  Old exams will be made available for review.
Bring a large (blue/gray) scantron sheet.  You will be allowed to bring statistical tables and one additional page (8½×11, both sides) of notes and formulas per exam.
Please see the exam policy below.
Exam Dates: Exam I: Friday, 20 February.  (subject to change)
Exam II: Wednesday, 1 April.  (subject to change)
Final Exam: Monday, 11 May, 3:30pm–5:30pm.
Grading Scale: A: 85% - 100%.
B: 75% - 84%.
C: 60% - 74%.
D: 50% - 59%.
Important Dates: Wednesday, 21 January – first day of class.
Monday, 26 January – last day to add or drop.
Monday, 16 March – first day of spring break.
Friday, 3 April – no class (reading day).
Tuesday, 21 April – last day to Q-drop or withdraw.
Tuesday, 5 May – last day of class (redefined Friday).

eCampus

Course Material: All students will have access to the lecture notes and handouts, homework assignments and other instructional materials at the eCampus website.
Instructions:
  1. Go to ecampus.tamu.edu.
  2. Click on Log In and log in with your NetID.
  3. Select STAT 212-502 in the My Courses module.
  4. Click on Discussions in the menu to the left to access the discussion board.
  5. Click on Content in the menu to the left for lecture notes, handouts, homework assignments and any other resources I may provide.

Course Policies

Homework Policy: Homework assignments will be downloaded from eCampus.
Your homework solutions must be your own work, not from outside sources, consistent with the university rules on academic integrity.  I expect you to follow this policy scrupulously.  Your exam performance is much more likely to be better.
You may use:
  • Your textbook, e-book, and notes from class.
  • Discussion with the instructor or lab assistants.
  • Voluntary, mutual and cooperative discussion with other students in the class.  Do not post solutions (anywhere).  Suggestions and partial explanations are ok.
You may not use:
  • Solutions manuals (printed or electronic) other than the student manual.
  • Solutions from students who took the class previously.
  • Simply copying from students in this class, including expecting them to reveal or provide their solutions in "discussion".  That is, you may work together as indicated above as long as you prepare your own solutions.
Homework is to be submitted by its due date unless I specify otherwise.  Late homework is not acceptable.
Exam Policy: Exams will be comprehensive and cumulative, and closed book.
Your exam solutions and answers must be your own work, consistent with the university rules on academic integrity.
Bring a large (blue/gray) scantron sheet for your answers.  Acceptable resources are:
  • A calculator for numerical calculations only.  The calculator may not be part of, associated with or connected to any communication device, such as a cell phone, iPod, tablet or laptop.
  • Statistical tables.  (Print your own copies.  I will have versions available online.)
  • One page (8½×11, both sides) of notes for the first exam, two pages for the second exam, and four pages for the final exam.  These must be of your own construction, not copied from somewhere or someone else.
No other resources are acceptable.
The discussion board will be off-limits on exam days.
No exam may be taken early or made up, except if you provide a university excused absence with appropriate documentation.
Copies of old exams will be available for you to review.  However, their content may not exactly match this semester's exams.
Classroom: Please turn off all communication devices (cell phones, iPods, etc.) while in the classroom.  You can have a calculator for in-class work.  A laptop or tablet is ok as long as you only use it to take notes or to view notes and handouts for this course.
Questions are encouraged, especially to help clarify points in the lecture.  No question is "bad" or "dumb" if it is relevant (although I do appreciate it if you listen and avoid asking a question just answered).
Help Session Lab Room: You are encouraged to take advantage of the help sessions in Blocker 162.  Various TAs will be available, depending on the time, but all are familiar with this and similar courses.
The laptops in the room are for statistics class use only.  Please be considerate of others.
Missed Work and Incompletes: This is based on university policy.
  • If you must miss an exam due to illness or circumstances beyond your control, notify me or the Statistics Department, in writing or by email (before, if feasible, otherwise within two working days after you return).  See me as soon as possible to schedule a make-up exam.
  • An Incomplete grade will be given only in the event that circumstances beyond your control cause prolonged absence from class and the work cannot be made up.

Course Outline

Topic Chapter
Introduction
I. Estimating Distributions 1, 4, 8
  a. histogram, density plot, box-plot (review)    1.1-1.4, 4.1
  b. cumulative distribution, quantile plot (review)    4.2, 4.6
  c. hypothesis testing (review)    8.1, 8.2, 8.4, 8.5
II. Regression and Correlation 5, 12, 13
  a. correlation and conditional expectation (review)    5.1-5.2
  b. straight line regression (review)    12.1-12.4
  c. inference for correlation    12.5
  d. checking for violations of assumptions    13.1
  e. polynomial and nonparametric regression, transformations    13.2-13.3
  f. multiple linear regression    13.4
  g. model selection and other issues    13.5
III. Design and Analysis of Experiments 9, 10, 11, 15
  a. completely randomized design (review)    10.1
  b. multiple comparisons and contrasts (review)    9.2, 10.2
  c. assumptions, transformations and Kruskal-Wallis test    9.3, 10.3, 15.2–15.4
  d. randomized block design, Friedman test    11.1, 15.4
  e. factorial experiments and interactions    11.2-11.4
  f. random and mixed effects models    10.3, 11.2
  g. general linear models, covariate analysis    
IV. Analysis of Categorical and Count Data 2, 3, 5, 8, 9, 13, 14
  a. one and two sample binomial procedures (review)    3.4, 3.6, 8.3, 9.4
  b. multinomial experiments    5.1, 14.1
  c. chi-squared goodness of fit test    14.1-14.2
  d. conditional probability, independence (review)    2.4-2.5
  e. contingency test, homogeneity test, McNemar test    14.3
  f. logistic regression    13.2
V. Methods for Percentiles 15
  a. sign test, tests for percentiles    15.1
  b. confidence intervals    
  c. median regression    

Copyright Information

Each document provided on these web pages is copyrighted by me (Daren B.H. Cline) with all rights reserved, whether or not the document explicitly states so.  These documents may only be used for academic purposes and they may not be reproduced, distributed or sold without my permission.  You may refer to them for other classes or for research, just as you would any book.