Table of Contents:
Plan of Course
First Part of Course
Making the Mastery Exam Work For You
Second Part of Course
Main Class Website: https://culearn.colorado.edu/webct/entryPageIns. dowebct
Time: 12:30-1:45 Tue,Thu, ATLAS 1B25 and Lab 5-6:30 Thu, ATLAS 1B25
Instructor: Gary McClelland
D347C Muenzinger, 303-492-8617
Office Hours: 1:10-3, Monday
WWW URL: http://psych.colorado.edu/~mcclella
Teaching Assistant: Heather Coulter
Office Hours: 2-3, Thursday
Textbook: McClelland, G.H. (2000). Seeing Statistics.
(online and free)
Goals of the Course
Making the Mastery Exam System Work for
You may take the Mastery Exam again if you fail it in order to pass Part I. However, you only have one shot at each Quiz and Homework assignment. This system is designed to put less pressure on you and to let you spend your time on learning rather than on worrying about your grades. Your letter grade is determined by the amount of work you do in Part II and is not affected by your score on the Mastery Exam, so long as you pass it. However, the better you do on the mastery exam, the easier Part II of the course is likely to be.
However, don't treat the Mastery Exam like a typical midterm or final. Cramming the night before by studying your notes and the text book will not work. The focus of this course is on learning by doing. The Exam will evaluate your ability to do statistics. The homework assignments and the quizzes are designed to give you feedback on your progress and to give you practice on the kinds of questions you will be expected to answer on the Mastery Exam.
If you are getting low quiz or homework scores, or are not understanding the lab or class material, or are feeling lost in any way, see your instructors IMMEDIATELY!! The material we cover in Part I is usually covered in a full semester in an old-style statistics course. You will also need to understand and be able to use this material in order to complete the second part of the course. Don't let yourself fall behind.
Second Part of Course
The purpose of Part II is to give you experience in applying the statistical concepts and tools you learned in Part I. You will be able to gain practical experience in all phases of the research process: posing questions, designing a statistical analysis to answer these questions, performing the statistical analyses, interpreting results, reviewing other's research papers, and revising your manuscripts to produce an excellent final product. Below is a brief description of the various activities; more details will be provided in a subsequent syllabus for Part II.
I will present the details of each of the activities described below, discuss other aspects of the research process such as publication, and hold workshops on the various activities and specific statistical techniques that might be of interest to certain students.
Research Manuscript and Article:
You will need to write your own APA-style research manuscript and article. To do this, you can explore a number of survey datasets that have already been collected and that I will provide for you. Alternatively, you can use data that is being collected in a lab you are working in or that you yourself have collected. You will gain practical experience in design, analysis, and interpretation of a series of research studies. For a C, you need to answer only one research question and use only one type of statistical analysis. To get an A, you must answer at least three research questions. These research questions should be on the same topic. This is often how research articles are written - a particular result inspires a new set of questions, which are then investigated in turn.
Your analyses, results,
and background research must be written up in an APA-style
manuscript, complete with title page, abstract,
Introduction, Methods, Results, Discussion, and References
sections. Your manuscript will be peer-reviewed by two of
your colleagues as well as the TA for the course. They will
provide detailed feedback to you so that you can revise your
manuscript and turn it in as a finished product, the
Research Article. Please note: the manuscript SHOULD NOT be
considered a rough-draft. It should be close to a final
product. If you submit a rough draft that is incomplete,
poorly organized, etc., the feedback you receive will suffer,
which will translate into a poor finished
The Research Article that you turn in will be a polished and quality piece of work, meaning that: a) your statistical analyses are appropriate, as are the conclusions you draw from them; b) the meaning of each sentence in your paper is clear; c) you say what you need to say but no more; d) your logic and conclusions make sense and are easy to follow; and e) you follow APA style exactly.
A central aspect of scientific research is peer review. Other scientists evaluate the quality of articles submitted for publication. We will simulate the publication process by having you be a journal reviewer of two other students' Research Articles. You should endeavor to provide detailed feedback to the author, letting them know precisely (e.g., page number, paragraph, and sentence) what is unclear, needs to be reworked, is confusing, or wrong. All aspects of the manuscript, from APA style to clarity of presentation to statistical analyses to conclusions drawn from them are fair game. Your job is not to provide a grade for the author; rather, it is to provide detailed feedback that will help the author to revise their paper into an excellent, clear, articulate article.
An important aspect of the scientific process is disseminating what you have learned to the wider scientific community. It is not enough to have discovered something interesting in your research; equally important is explaining it to others through presentations and publications. In this activity, you will give a short (~ 10 min.), in-class presentation about your project in the style of presentations at scientific conventions.
For the most part, you determine your own grade in this course by choosing how much work that you decide to do. The table below gives the activities required for a given grade. This does not mean however that you can turn in sub-par work and receive a certain grade. If you are going for an "A," it is expected that you do "A" quality work in your presentation, peer review, and (especially) your research article (your research manuscript does not count towards your grade unless you are going for a "C"; however, it is very much in your self-interest to submit a quality manuscript in order to get back useful feedback). If any of the three activities do not meet this expectation, your final grade will be lowered by a half step, with research article counting double. For example, if you are going for an A, your base grade starts at an A and I fully expect that this will be your final grade. If however your peer review is only B quality, your final grade will be lowered a step to an A-; if C quality, your final grade will be a B+. Research articles are doubly important, so if it is B quality, your final grade would be a B+; if C quality, it would be a B-, and so forth. Truly fantastic work will merit similar increases in grades.
Disabilities, Learning Difficulties, and Related
The flexible structure and small size of this course makes it easy to accommodate a wide range of learning-related difficulties. Please send me an email or talk to me in office hours about any special problems you may have.
Religious and Other Absences
Similarly, the flexible structure and small size of this course makes it easy to accommodate absences for religious observances, medical appointments, or similar needs. Please send me email or talk to me in office hours about any absences you will need and we will make arrangements.
Students are expected to know and comply with University policies described by these links:
Responsible Computer Use
Classroom and Course-related Behavior
Index of all University Policies
Aug 24 - CLASS 1 - Introductions, syllabus, and overview
Aug 26 - CLASS 2 - Basic concepts. Have read SS Ch. 0 & 1
Aug 26 - LAB 1 - Basics of R.
Aug 31- CLASS 3 - Descriptive statistics. Have read SS Ch. 2-5. HW #1 (basic concepts) due.
Sep 2 - CLASS 4 - Sampling distributions. Have read SS Ch. 6-8.
Sep 2 - LAB 2 - Descriptive statistics in R.
Sep 7 - CLASS 5- Sampling distributions part II & statistical decisions. HW #2 (descriptive stats) due
Sep 9 - CLASS 6 - 1-sample, indep., and paired t-tests. Have read SS Ch. 9 & 10.
Sep 9 - LAB 3 - t-tests and graphs in R.
Sep 14 - CLASS 7 - Research design. HW #3 (means and t-tests) due. Quiz 1.
Sep 16 - CLASS 8 - Correlation and regression. Have read SS Ch. 12.
Sep 16- LAB 4 - Correlation and regression with graphs in R.
Sep 21- CLASS 9 - Regression. HW #4 (correlation and regression) due.
Sep 23 - CLASS 10 - Regression practicals.
Sep 23 - LAB 5 - Correlation and regression with graphs in R
Sep 28 - CLASS 11 - Multiple regression part I. HW #5 (Regression) due.
Sep 30 - CLASS 12 - Multiple regression part II in R.
Sep 30 - LAB 6 - Multiple regression in R.
Oct 5- CLASS 13 - Multiple regression: interactions. HW #6 (multiple regression II) due. Quiz 2.
Optional reading: http:// www.jerrydallal.com/LHSP/reginter.htm
Oct 7 - CLASS 14 - ANOVA from a regression standpoint.
Oct 7 - LAB 7 - ANOVA and interactions in R.
Oct 12 - CLASS 15 - Factorial ANOVA using regression. HW #7 (interactions & ANOVA) due.
Oct 14- CLASS 16 - Factorial ANOVA part II.
Oct 14- LAB 8 - Factorial ANOVA in R.
Oct 19- CLASS 17 - Factorial ANOVA part III. Have read SS Ch. 8-10. HW #8(ANOVA) due.
Oct 21 - CLASS 18 - Logistic regression.
Oct 21 - LAB 9 - Find articles online. APA bibliographic format.
Oct 26 - CLASS 19 - Review for Mastery Exam
Oct 28- CLASS 20 - Mastery Exam - Closed-book portion.
Oct 28 - LAB 10 - Mastery Exam - Open book portion.
Mar 23 - Fall Break - no classes
Mar 25 - Spring Break - no classes
Nov 2- CLASS 21 - Mastery Exam results. Overview of Part II
Nov 4 - CLASS 22 - Work on Research Project
Nov 4 - LAB 11 - Coding data in R. Work on Research Project
Nov 9 - CLASS 23 - Work on Research Project
Nov 11 - CLASS 24 - Work on Research Project
Nov 11 - LAB 12 - Work on Research Project
Nov 16 - CLASS 25 - Work on Research Project
Nov 18 - CLASS 26 - Work on Research Project
Nov 18 - LAB 13 - Work on Research Project
Nov 23 - Fall Break - no classes
Nov 25 - Spring Break - no classes
Nov 30 - CLASS 27 - Work on Research Project
Dec 2 - CLASS 28 - Research Project Presentations. Last possible day to turn in Research Manuscript.
Dec 2 - LAB 14 - Research Project Presentations.
- Dec 7 - Research Project Presentations.
Dec 9 - CLASS 30 - Research Project Presentations. Last possible day to turn in Peer Reviews.
Dec 9 - LAB 15 - Research Project Presentations.
Dec 11 - REVISED RESEARCH ARTICLE & RESPONSE TO COMMENTS DUE BY 5PM
NOTE: These course materials are a collaboraive effor between Gary McClelland and Matt Keller. Gary developed the basic structure for this course and refined it over the years. Matt Keller has recently refined and improved the structure. And now Gary is hoping not to mess it up too much.
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Last Modified: Mon, Aug 23, 2010, 1:17 pm