Syllabus for PSY 138:
Reasoning in Psychology Using Statistics

Fall, 2005

Contact Information

Teaching Assistants (TAs)

Reasoning in Psychology Using Statistics uses a classroom/laboratory approach for analysis of data, for hands-on production of data, and for simulation-based learning. According to Cobb (1993, p. 4), "the lab approach accords with the movement of statistics back towards its roots in science, and with research in education that demonstrates the importance of active learning." Additionally, the classroom/lab setting allows students to access the vast array of data available through the Internet.

Reasoning in Psychology Using Statistics follows the guidelines developed by the American Statistical Association (ASA) and the Mathematical Association of America (MAA) which suggest that teachers should:

• Motivate students by showing them statistics at work in real applications, problems, cases, and projects.
• Use real data and statistical computing (SPSS).
• Downplay formal training in probability in favor of intuitive concepts of probability.
• Foster active learning

The student will have the opportunity to:

• Understand basic statistical reasoning. Statistical methods provide powerful analytic tools for almost every human enterprise that can state its observations in numbers. A critical understanding of statistics -- its limitations as well as its potentials -- is almost as essential for living as is the ability to read and write.
• Gain access to existing knowledge by:
• locating published research in psychology and statistics and related fields;
• locating information on particular topics and issues in psychology;
• searching out psychological data as well as information about the meaning of the data and how they are derived.
• Display command of existing knowledge by
• locating specific information in published psychological articles;
• evaluating methodology used in psychological studies;
• explaining key psychological and statistical concepts and describe how they can be used.
• Learn by doing, i.e., manipulate real data using SPSS (a statistical computing program) and explicate a number controversies that are currently in the news, in a team setting.

Textbook (Required)

Software

Class Time

Your grade will be determined by summing your performance on homework, Mallard quizzes, in-class labs, exams, and projects.

• Lab Assignments: Every lab (except exam days) will include a web-based lab assignment. These labs will include both group and individual exercises. Each of the labs will be described in a web page. Included on each lab webpage will be a "lab worksheet." These worksheets are MS Word files into which you will need to type (or in some cases "copy" and "paste") your answers. Any portion of lab assignments not completed during lab time are HW and are due at the beginning of the next lab. BEFORE the beginning of the next lab period, you should save your worksheets to disk, and print out a copy of the worksheet to turn into your instructor. Lab solutions will be available on the Mallard course page (go to Lessons page in Mallard) after they are due. It is your responsibility to check the solutions to understand errors in your lab work.
• In-class Quizzes: There will be a total of 12 in-class (lecture) quizzes. Quizzes will be given on random days at the end of the lecture period. No make-up quizzes will be given for any reason! Therefore, if you miss class the day a quiz is given, you cannot make up the quiz. Extra credit is available if you wish to supplement your final grade in the course (see below).
• Homework Problems: Each week you will be assigned some exercises from your reading packet. Due dates are listed below. Click here for a list of HW problems for each assigned homework.
There will be 14 homeworks assigned with conceptual or computational problems to complete. Homework solutions will be available on the Mallard course page (go to Lessons page in Mallard) after they are due. It is your responsibility to check the solutions to understand errors in your homework problems.
• Exams: There will be three exams. They are cumulative to the extent that the material from later parts of the class build upon material from the early parts. These exams may include both conceptual and compuational questions. The format will typically be both multiple choice and short answer. The portion of the exams given in lecture will be closed-book. Portions given in lab will be open-book. More information will be given in class.
• Projects: There will be two projects for the course. Each project is designed to apply the principles of statistics to a realistic research project. Project assignment sheets are in your reading packet and due dates are listed below. Project #1 will require you to conduct library research to find articles, read the articles, and answer questions about the content of the articles. For Project #2 you will be given a brief description of a research project with a set of data. Your task will be to analyze the data set and to write a written summary of the results of your analyses. Project descriptions and data sets for Project #2 will be posted on the course web pages. Ask me or your TA for help on the projects if you need it.

Each exam is worth a maximum of 175 points (525 total)
Your homeworks are worth 10 points each (140 total).
Each in-class quiz is worth a maximum of 5 points (60 total).
Each lab is worth 2.5 points (65 total).
Your projects are worth 90 & 120 points (210 total).

Therefore, there is a total of 1000 possible points. Grades are determined from a straight percentage scale. Your final semester grade will be determined from your total points out of 1000 possible points:

                      
Point Total        Grade
                      
900-1000           A
                      
800-899            B
                      
700-799            C
                      
600-699            D
                      
000-599            F

You must earn at least the lowest point total in these ranges to earn a particular grade. No curving or rounding will be done for grading. Extra credit is available if you wish to help boost your point total (see the extra credit section for important information), but all extra credit must be turned in by the day of exams (see schedule below for exam dates).

Grade records for this course will be kept on the secure web server (Mallard) that you may access during and after the semester to check your grade progress. You will be given a login and password (that you may change the first time you log in) to access your grade. Once you change your password, no one else will have access to your password or be able to view your grades. If you forget your password, come see me to have a new one assigned (which you may then change). The grade server may be accessed from the course web page.

You may earn up to 50 points of extra credit in two ways:

(a) You may volunteer to participate as a subject in psychological research.  You may earn 5 extra credit points for each half hour of participation (10 points per hour) if you choose to volunteer, for a maximum of 50 points (5 hours total). Participation as a research subject is entirely voluntary. To sign up for an experiment, go to the basement of DeGarmo Hall and sign up on the sheets posted on the bulletin board.  Please respect the sign-up process by keeping appointments and only signing up for each experiment once. Please read the participation guidelines before signing up for an experiment. You will receive a blue card with your participation time circled. Blue cards may be used in one class only to earn extra credit.
 
(b) You may write up to five journal article summaries for extra credit. The articles may be on a topic of your choice, but must come from Psychological Science (a psychology journal that covers a range of topics). Articles must be Research Reports or Research Articles from this journal. Summaries should be approximately 3 pages in length and typed with double spacing. The article must accompany each summary you hand in and it must be written in your own words to receive credit. Each summary may earn a maximum of 10 pts of extra credit. You will not earn any extra credit points for summaries written on articles that are not research reports or articles from Psychological Science.

Extra credit will be added to exam scores. Therefore, extra credit that you'd like to add to an exam score must be handed in in lecture (not lab) the day of the exam. So extra credit is due on 9/19, 10/24, and 12/15. You may add a maximum of 25 points of extra credit to any exam. Your grade will not be affected if you do not choose to participate in one of the extra credit options. You may only earn a total of 50 extra credit points toward your final grade in the course no matter which option you choose. Extra credit assignments will be held to academic dishonesty standards like any other assignment. If you plagiarize an article for extra credit, you will not earn any points for that summary (and I check them carefully so be sure to complete summary assignments in your own words).

No make-up quizzes or exams/projects will be given unless you have a documented emergency AND you contact me before the exam or assignment is due.

A 10% off per day late penalty will apply to all late assignments except HW (see Late Policy below).

The course contract is considered final. The work necessary to obtain the grade you desire has been outlined here. No additional work will be accepted to increase your grade. Do not come to me at semester's end asking if there is some additional work you can do to increase your grade. At semester's end, there is none. You have the opportunity to complete extra credit according to the guidelines listed above. No additional extra credit will be allowed at the end of the semester.

Late Policy

Homework assignments can be submitted late for 1/2 credit (maximum of 5 points). If you will miss a class when a HW is due, you should turn it in BEFORE class to my box in DeG 435. Make sure my name is on the front. Labs cannot be submitted late or early unless you clear it with me first and only emergency situations will be considered for make-up labs. All labs will not be eligible for make-up as some include group project components. All other assignments will be held to a 10% point penalty per day it is late. If you have any questions about late assignments, please ask me. Do NOT assume an assignment can automatically be turned in late.

Because this is an active learning class, daily attendance and active participation with your classmates in discussions, problem solving, and computer work is absolutely essential if you are to master the key statistical concepts taught in this course. As a result, participation is NOT optional -- you are expected to attend and participate in every class and lab. Because you can't participate if you do not attend, only official university excused absences will be considered and labs must still be completed before the due date to receive credit. Labs will extend (rather than repeat) material covered in lecture. Therefore, if you miss a lecture, the lab may be difficult for you to complete during lab time. Do not expect your lab instructor to teach you material you miss in lecture. It is your responsibility to get notes from someone in class and prepare for lab exercises.

Keep up with your reading assignments. Do the homework. Use class presentations as a guide to the most important material. Use your team as a study group to work on assignments outside of class. Note: a major finding of the Harvard Assessment Seminars concerns the value of small groups to enhance students' learning, "in every comparison of how much students learn when they work in small groups with how much they learn in large groups or when they work alone, small groups show the best outcomes. Students who study in small [study] groups do better than students studying alone. The payoff comes is a modest way for student achievement, as measured by test scores. It comes in a far bigger way on measures of students' involvement in courses, their enthusiasm, and their pursuit of topics to a more advanced level. And students overwhelmingly report one additional benefit of small group work. They point out that the process of working in a group, in a supervised setting, teaches them crucial skills. The skills they learn include how to move a group forward, how to disagree without being destructive or stifling new ideas, and how to include all members in a discussion. Students should think twice if they find themselves spending all their time working alone."

Please visit me during my office hours (Tues and Weds 2-3 pm) with any questions you have. My job is to help you learn. If you need help, get it early; don't wait until you are "so lost I don't know what to ask!" If you cannot make it to my regular office hours then you are welcome to make an appointment with me. Talk to me after class, call me (438-7146), or e-mail me at: dmcbride@ilstu.edu (of these last two options, e-mailing will get you the faster answer). You can also talk to the TAs if you need help. They will hold office hours each week that you are welcome to attend. Their hours and desks are listed above under Contact Information. You can also e-mail them at the addresses listed above.

Extra assistance

Any student needing to arrange a reasonable accommodation for a documented disability should contact Disability Concerns at 350 Fell Hall, 438-5853 (voice), 438-8620 (TDD).

Course Outline

If you have any questions, please feel free to contact me at dmcbride@ilstu.edu.

If you are interested in obtaining research experience in human memory, take a look at the Memory Lab page.