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Introduction to Statistics
Psychology 15.1
Fall 1999
TR 11:15 - 12:30 258 Willard Bldg.
W 11:15 - 12:05 64 Willard Bldg.
W 12:20 -1:10 258 Willard Bldg.



Instructor: Andrew Peck, Ph.D.
Office: 350 Moore Bldg.
Phone: 865-1838
Office Hours: M & F 10:15-12:00 and by appointment
E-mail: acp103@psu.edu
 

Classwork TA: Laurie Cashman (McGrath)                                      Lab TA: Analea Brauburger
Office:                                                                                                  Office:
Phone:                                                                                                  Phone:
Office Hours:                                                                                      Office Hours:
E-mail: lac208@psu.edu                                                                     E-mail: alb290@psu.edu
 

Prerequisites
The student MUST have an understanding of basic mathematical concepts to succeed in this course. Such concepts include: addition, subtraction, multiplication, division, squares, squareroots, and the proper use of parentheses. Students should also have a basic understanding of area, graphs, charts, tables, and computers.
 

Required
Pagano, R.R. (1998). Understanding Statistics in the Behavioral Science. (5th Ed.) California: Brooks/Cole Publishing Company

Norušis, M.J. (1999). SPSS 9.0 Guide to Data Analysis. New Jersey: Prentice Hall.

A portable calculator that will allow you square numbers and find the square root of numbers (do NOT purchase a calculator that is too to figure out!!)
 

Optional
Follette, W.C., and Pagano, R.R. (1998). Study Guide to Accompany Understanding Statistics in the Behavioral Science. (5th Ed.) California: Brooks/Cole Publishing Company
 

Course Purpose
To introduce students to the fundamental statistical concepts that provide the foundation for psychological theory, methodology, and research

To introduce students to statistical computer programs (SPSS 9.0) psychologists use to analyze data

To prepare students for courses in research methodology (e.g., Psy 201) and more advanced courses in statistics
 

Course Objectives
After taking this course students should be able to understand fundamental statistical concepts, solve related equations, and perform preliminary data analyses by hand and with SPSS 9.0.

Students should gain a better understanding of both psychology as a science and the procedures and decisions involved in testing hypotheses and making conclusions about human behavior.
 

Web Support
To devote more attention to listening and less to actual note taking some students like to bring copies of lecture notes to class and add to them during the lecture. This semester lecture notes will be available on the web at http://www.yournotes.com. Please feel free to use these notes as a study aid, but realize that they cannot replace class attendance and active learning.
 

General Policies
Questions during class are encouraged. If you don't understand something please ask, chances are that other people have the same question.

No appointment is needed to see me during office hours, although you may have to wait while I talk with other students. If you can not make my office hours please see me to make an appointment. After class is usually a good time to ask brief questions. I welcome student concerns and questions, so if you have one about any aspect of the course please ask.

The Pennsylvania State University encourages qualified people with disabilities to participate in its programs and activities. If you anticipate needing any type of accommodation in this course or have questions about physical access, please tell the instructor or TA immediately.

Please do not call me at home. The best way to contact me outside of class is through e-mail.
 

Earning your Grade
Student grades will be based on exam grades, course homework grades, class participation, lab work grades, and extra credit.

Exams: Tests will consist of two parts. The first part will be closed book and will address concepts and ideas. The second part will be open book and will involve the analysis of data by hand (and calculator). There will be 4 tests: 3 in-class tests and a final exam. Each exam is worth 100 points. Exams may cover lecture material not covered by the book, book material not covered in class, and lecture material covered by the book. The availability and format of make-up exams is at the discretion of the instructor. In the event of University-approved absences or medical problems, please see the instructor to discuss making up missed exams. In general, advance notice or appropriate documentation (e.g., doctor's note) will be required to schedule a make-up exam.

Course homework: You will have homework. Sometimes you'll have a lot of it. In a course like this practice is key to learning and understanding. Homework MUST be handed in on time to earn credit. Feel free to do homework with a friend if you think it will help. In the event of University-approved absences or medical problems, please see the instructor to discuss making up or handing in late homework. Course homework will be worth 100 points.

Class Participation: On Wednesdays we'll meet to go over homework. Because psychological research has shown that people learn more in more active environments, everyone will be required at some time to go to the board and demonstrate their solutions to homework problems - NO EXCEPTIONS. Class participation is expected and is not worth any points. Each time you are called on to participate and you are not in class you WILL LOSE 2 POINTS. Each time you are called on and you are not prepared to participate you WILL LOSE 2 POINTS.

Lab work: On Wednesdays we'll meet in the computer lab (64 Willard Bldg.). This time is set aside for you to learn SPSS 9.0. You will be required to do reading and homework for this portion of the course. Lab homework MUST be handed in on time to earn credit. Feel free to do lab work with a friend if you think it will help. In the event of University-approved absences or medical problems, please see the instructor to discuss making up or handing in late lab homework. Lab homework will be worth 100 points.
 

Extra Credit: Students can ear up to 15 points of extra credit by:

1) ...participating in research. Often students are needed to participate in research experiments conducted by Penn State faculty and graduate students. Students can earn up to 15 points of extra credit by participating in psychology experiments. You can sign up for available experiments on the web by accessing the Department of Psychology home page (http://psych.la.psu.edu.) and selecting 'Participate in Research'. You will be required to provide your student number. You will receive 1 point for each experiment that you do unless the experiment takes more than 1 hr. If the experiment takes more than 1 hr. you will receive 1 point for each hour you participate.

2) ...reviewing a new web site. Recently a new web site has been introduced to help students understand statistics through visualization. Our class has been selected to beta test the site. You can earn 1 point of extra credit by going through a seeing statistics lesson and writing a 1 page essay about the lesson. What did you find helpful? Confusing? Should they restructure anything? If so, what? Be specific enough to show that you actually did the lesson, or no credit will be awarded. Lesson write-ups are due the day the corresponding material is tested. The address is seeingstatistics.com. When you arrive click the enter button. Our User Name is seestats. Our password is checkerboard. Be patient, sometimes screens are slow to load.

3) ...doing a PsychSim module. Do the PsychSim module on "Central Tendency and Variability" or "Correlation," or do both. Fill out the appropriate worksheet while completing the module. Each correctly completed worksheet is worth 1 point. PsychSim is accessible only from PSU computer terminals. Use the "Find" option to locate the PsychSim and then select the appropriate module. PsychSim worksheets can be printed from the class web site. Completed PsychSim worksheets must be handed in before the corresponding material is tested.
 

Academic Integrity
Students are responsible for maintaining academic integrity. Violations include cheating on exams, removing exams from the classroom without consent from the instructor, and dishonesty in any aspect of course participation. Violations of academic integrity may result in a grade of F for the course as well as other penalties. All such violations will be handled in the strongest manner permitted under University policy (Faculty Senate Policy 49-20).
 

Grade Breakdown
 
Percentage
Grade
93-100
A
90-92
A-
87-89
B+
83-86
B
80-82
B-
77-79
C+
70-76
C
60-69
D
00-59
F

Important Dates
September 16 - Exam 1
October 12 - No class - Fall Break
October 19 - Exam 2
November 16 - Exam 3
November 25 - No class - Thanksgiving Break
December 9 - Last day of class
December 13 - 17 - Final Exam - Date and time determined by the University
 
 

Tentative Course Outline

Topic
Pagano Reading

 

See Stats Reading (optional)

 

Introduction
Chapter 1
Introduction
Concepts and Measurement
Chapter 2
Data and Comparisons
Frequency Distributions
Chapter 3
Seeing Data
Measures of Central Tendency
Chapter 4
Describing the Center
Dispersion and Variability
Chapter 4
Describing the Spread
Normal Curve and Standard Scores
Chapter 5
Normal Distribution
Correlation
Chapter 6
Correlation and Regression
Linear Regression
Chapter 7
Correlation and Regression
Probability
Chapter 8
Probability
Hypotheses Testing
None
None
Normal Deviate (z) Test
Chapter 12
Inference and Confidence
Student's t Test for Single Groups
Chapter 13
One Sample Comparisons
Student's t Test for Multiple Groups
Chapter 14
Two Sample Comparisons
Introduction to ANOVA
Chapter 15
Multigroup Comparisons

 
 

Tentative Lab Outline

Topic
SPSS 9.0 Reading

 

Introduction
Chapter 2
Counting Responses
Chapter 3 
Looking at Distributions
Chapter 6 
Computing Descriptive Statistics
Chapter 4 
Comparing Groups
Chapter 5 
The Normal Distribution
Chapter 10
Plotting Data
Chapter 8
Linear Regression and Correlation
Chapter 19
Testing a Hypothesis About a Single Mean 
Chapter 11
Testing a Hypothesis About 2 Related Means 
Chapter 12
Testing a Hypothesis About 2 Independent Means
Chapter 13
One-way ANOVA
Chapter 14

 
 
 
Information contained on this page does not represent the lecture verbatim.
These notes are not a substitute for class attendance.



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