Request for Designation As a Quantitative Analysis (QA) Course in Explorations

Request for Designation as a Quantitative Analysis (QA) Course in Explorations

Name____Tricia Witte

Course number and title____PY204______

Departmental endorsement______

Has this course been submitted for any other Explorations designation? ____NO______
If so, which one? ______

Please list which of your course assignments or activities addresses each of the guidelines, state briefly how this is accomplished, and attach a syllabus or a preliminary redesign plan for the course.

Criteria for a course in quantitative analysisadvocates a method of inquiry which

Frames a problem quantitatively by transferring information or data into a mathematical or statistical model or formal notation

Regularly assigned textbook and laboratory assignments require students to answer research questions (e.g., Does Ritalin enhance attention? Does the presence of other people inhibit helping in an emergency situation?) using statistical methods (e.g., t-test, ANOVA).

Solves the problem using mathematical concepts and strategies, with the aid of technology where appropriate

Using calculators in the classroom and advanced statistical software (i.e., SPSS) in the lab, students are given class examples, textbook assignments, and laboratory assignments that require the use of statistical methods (e.g., t-test, ANOVA) to reach conclusions. For example, for one laboratory assignment students are provided data for a mock drug trial (e.g., placebo versus active drug) and they test the efficacy of the drug using the data provided.

Thinks critically about the quantitative results and interpret them in the context of the original problem

Students critically think about quantitative results of any given study by testing whether the results could occur in the general population by chance alone, and then using these findings to support or reject the original hypotheses.

Clearly communicates findings

Every lab assignment, as well as the final lab project, requires a formal write-up using APA style, which includes a general description of the findings including the statistics used to reach such conclusions.

Return this form as one electronic file with a syllabus appended to by 30 May 2011.

PY204, PY204L

Statistics for Research

Lectures: Mon, Wed 2:00 / Lab: Wed 3:30

Professor: Dr. Tricia Witte
Office: 317 Harbert Hall
Phone: 205-226-4832
Email: / Office hours:
Monday 1 - 2
Tuesday by appointment
Wednesday 10 - 11
Thursday 2 - 3

Required Materials

1) Witte, R. S., & Witte, J. S. (2010). Statistics, Ninth Edition. Wiley.

2) Yockey, R. D. (2011). SPSS Demystified: A Step-by-Step Guide to Successful Data Analysis, Second Edition. Prentice Hall.

3) Calculator (any calculator – but not one on your cell phone)

4) Access to a computer with PASW/SPSS (Harbert Lab 301)

Recommended Materials

1) The student companion website for the text -

2) APA (2010). The Publication Manual for the American Psychological Association, 6th edition.

Course Description and Objectives

Research in psychology relies heavily on statistical methods to interpret data. For example, psychologists use data and statistical methods to figure out if men really are different from women, or if rats run through mazes much faster after being injected with caffeine. By the end of this course you should be able to:

1) Understand a variety of statistical concepts

2) Understand how to apply appropriate statistical methods to summarize & analyze data

3) Understand how to interpret the results of statistical analyses

Course Structure

You’ll meet twice a week in the classroom (e.g., lecture, practice problems, calculations by hand, etc.) and once a week in the computer lab where you will learn how to conduct statistical analyses using the SPSS computer software. At some point during the first few weeks, you will begin to wonder why you are wasting time solving complex statistical problems by hand when computer software is readily available! I assure you, it is for your own good. You will gain a deeper understating of the concepts if you have to solve them by hand. It is extremely important for you to attend every class and complete every assignment (even if you have the urge to throw your textbook out the window!). In fact, missing even one class or one assignment will increase the probability that you’ll feel “lost” for the rest of the semester. Please do not attempt to learn the material by reading the text without being present for the accompanying lecture.

Expectations

You will be expected to do the following:

(1) attend class and actively participate in class discussions

(2) complete various assignments

(3) take several exams

(4) complete one group project.

Grading

Class Assignments 20 points

Lab Assignments 80 points (8 graded labs)

Exam 1100 points

Exam 2100 points

Exam 3100 points

Group Project100 points

TOTAL =500 points

Attendance Policy

I expect you to attend every class. If you miss 0 or 1 class, you will earn 5 points extra credit at the end of the term. If you miss 6 or more classes, you will fail the course. There are no excused absences.

Class Assignments

Class assignments are paper-and-pencil assignments from the textbook. You will be able to find most of the answers to the assigned questions in the back of your textbook. Class assignments are due EVERY MONDAY IN CLASS. They must be turned in at the beginning of class in paper form. You may NOT work with a peer on these assignments. Late assignments will NOT be accepted. However, you have one “free pass” that you may use on a single late class assignment. This free pass will allow you to turn in any single assignment within 24 hours after it was originally due, and it will be accepted as if it was turned in on time. If you turn in all of the class assignments, you will earn 20/20. If not, the following is the breakdown of grades:

Failure to turn in 1 assignment = 15/20

Failure to turn in 2 assignments = 10/20

Failure to turn in 3 or more assignments = 0/20

Lab Assignments

Lab assignments require the use of SPSS in the Harbert computer lab (HB301). Lab assignments are due EVERY WEDNESDAY IN LAB. They must be turned in at the beginning of lab in paper form. You may NOT work with a peer on these assignments. Late assignments will NOT be accepted. However, you have one “free pass” that you may use on a single late lab assignment. This free pass will allow you to turn in any single assignment within 24 hours after it was originally due, and it will be accepted as if it was turned in on time. Each lab will be worth 10 points.

Exams

Exams will cover everything you learn in the “lecture” portion of class, but not the lab component. Exam 3 is not meant to be a cumulative final exam; it will cover the final third of class. However, the topic of multiple regression (which will be on Exam 3) covers many of the topics that you will learn throughout the term, so be prepared to study for Exam 3 as if it were a cumulative final exam. It is expected that you will take all exams as scheduled. Please let the instructor know at least 1 week (7 days) ahead of time if you know that you will miss an exam so an alternative time for you to take the exam can be scheduled (with no penalty). However, if you miss an exam without notifying the instructor at least 1 week ahead of time, you will be able to make up the exam, but there will be a 10% penalty. So, to sum up: miss with sufficient notice = no penalty, miss without sufficient notice = penalty.

Group Project

This group project is, in essence, your final exam because it is CUMULATIVE! In other words, you will need to use information from the entire course to complete this project. You will be given a data set and a list of research questions to answer. You will answer each research question using SPSS and write your results in APA format.

Appropriate classroom behavior

I expect appropriate behavior at all times in my classroom. I tend to be laid back and casual for the most part, and I encourage you to feel relaxed and comfortable in my class. However, there are certain behaviors that demonstrate respect, maturity, and intellectual engagementand other behaviors that are downright inappropriate. Below are some examples of appropriate and inappropriate classroom behavior.The list is not exhaustive. I expect that you will use common sense to judge whether or not a behavior is inappropriate. You may be asked to leave the classroom if you engage in inappropriate classroom behavior.

Appropriate behaviorInappropriate behavior

Paying attention to the current lecture or class discussion / Talking or texting on cell phone, talking or whispering to a classmate when the instructor or another student is talking, falling asleep
Raising your hand or waiting your turn to speak / Interrupting the professor or a student
Turning in an assignment on time and in an appropriate format / Turning in assignments late or in a sloppy manner
Coming to class on time and prepared (e.g., having read the assigned readings, etc.) / Whining about how much work is required or the grade you earned, etc.
Asking questions or offering comments that help facilitate classroom discussion / Answering too many questions or otherwise monopolizing the time in class so other students don’t have a chance to speak

Academic Integrity

Any violation of BSC’s Honor Code (e.g., cheating, plagiarism) will lead to a failing grade on an assignment, exam, or course (at the instructor’s discretion). Additional sanctions may be given by the Honor Council. It is your responsibility to learn about the Honor Code and Honor Council as well as the various ways to violate the Honor Code. Please go to the following website:

Academic Accommodations

Please see me if you have any concerns about your ability to perform well in this course. If you have a documented disability and require accommodations, please complete a “Request for Academic Accommodation” form (these forms can be obtained from the Director of Personal Counseling at the Norton Campus Center).

CLASS SCHEDULE (tentative)

Date Topic Due

W 2/2 / Review syllabus
W 2/2
Lab / No lab
M 2/7 / Introduction, tables, graphs, central tendency, variability (Witte Ch 1 – 4)
W 2/9 / Tables, graphs, central tendency, variability
W 2/9 Lab / Introduction to SPSS
M 2/14 / Normal distribution and standard scores (Witte Ch 5) / Assignment #1 (Witte Ch 1, 2, 3)
W 2/16 / Normal distribution and standard scores
W 2/16 Lab / SPSS functions and descriptive statistics / Lab A – Introduction to SPSS
M 2/21 / Correlation and simple regression (Witte Ch 6 – 7) / Assignment #2 (Witte Ch 4, 5)
W 2/23 / Correlation and simple regression
W 2/23 Lab / Correlation and simple regression / Lab #1 – SPSS functions and descriptive statistics
M 2/28 / Review / Assignment #3 (Witte Ch 6 – 7)
W 3/2 / CLASS EXAM 1
W 3/2 / Practice / Lab #2 – Correlation/Regression
M 3/7 / Hypothesis testing with z-test and one sample t-test and estimation (Ch 9 – 13)
W 3/9 / Hypothesis testing with z-test and one sample t-test and estimation
W 3/9 Lab / One-sample t-test (Yockey Ch 5)
M 3/14 W 3/16 / SPRING BREAK
M 3/21 / Independent samples t-test (Ch 14) / Assignment #4 (Witte Ch 9 – 13)
W 3/23 / Independent samples t-test
W 3/23
Lab / Independent samples t-test (Yockey Ch 6) / Lab #3 – One sample t-test (Yockey Ch 5)
M 3/28 / Paired samples t-test (Ch 15) / Assignment #5 (Ch 14)
W 3/30 / Paired samples t-test
W 3/30 Lab / Paired samples t-test (Yockey Ch 7) / Lab #4 – Independent samples t-test (Yockey Ch 6)
M 4/4 / Review / Assignment #6 (Witte Ch 15)
W 4/6 / CLASS EXAM 2
W 4/6 / Practice / Lab #5 - Paired samples t-test (Yockey Ch 7)
M 4/11 / One-way ANOVA (Ch 16)
W 4/13 / One-way ANOVA
W 4/13
Lab / One-way ANOVA (Yockey Ch 8)
M 4/18 / Factorial ANOVA (Ch 18) / Assignment #7 (Witte Ch 16)
W 4/20 / Factorial ANOVA
W 4/20 Lab / Factorial ANOVA (Yockey Ch 9) / Lab #6 – One-way ANOVA (Yockey Ch 8)
M 4/25 / Multiple regression / Assignment #8 (Witte Ch 18)
W 4/27 / Multiple regression
W 4/27 Lab / Multiple regression (Yockey Ch 12, 13, 14) / Lab #7 – Factorial ANOVA (Yockey Ch 9)
M 5/2 / Review / Assignment #9 (Multiple Regression)
W 5/4 / CLASS EXAM 3
W 5/4 Lab / Work on projects / Lab #8 – Multiple Regression (Yockey Ch 12, 13, 14)
M 5/9 1:00pm / Turn in projects / FINAL PROJECT DUE at 1:00pm