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PSYC 2240 Statistics: Home

Course Description

Course Syllabus

Syllabus: PSYC-2240 - 01


Course Description:  Behavioral Statistics – CRN/ 5203

    A Statistics course in the social or behavioral sciences introduces the techniques that allow researchers and investigators to identify potentially meaningful changes or differences in real word events.

Section Instructor: Dr. Clarence Rohrbaugh


Office: 230 Hardway Bldg.    Phone: 367-4669    Office Hours: M-F 9am / before or after class other times by appointment

Course Information:  

Time:    Mon.-Thur. 9:00am – 11:00am             Location:  online
Book: Introductory Statistics, by Barbara Illowsky and Susan Dean. Free downloadable or online
Hardware and Software needs:

* An inexpensive calculator with a square root key. The book uses a TI84 for examples.
* A computer with Internet access
* A browser compatible with Blackboard
* Microsoft Word, Corel WordPerfect, Wordpad or other word processing software that allows you to save your files in Rich Text Format (.rtf)
* Adobe Acrobat Reader
* Virus Protection Software - Blackboard's mail, discussion, and assignment tools use file submission. Files may contain viruses. It is your responsibility to protect your own computer.

Attention -  You should expect to spend 10-14 hours per week on work for this course (Summer courses are completed in 5 weeks which means you should spend a minimum of 30hrs per week on course materials. This is not a joke.)  All phones and text messaging devices must be turned off during class. All courses are subject to audio and/or video recording. All online connections are logged.
LibGuides on the Library web page is used to provide additional resources for this class.

Course Outcomes:
By the end of the semester, students will have the skills to:

1. Analyze a set of data 2. Construct frequency distributions and graphs from data 3. Work with probability distributions 4. Conduct one- and two-tailed t-tests on data 5. Set up and test a null hypothesis 6. Perform an analysis of variance 7. Perform simple correlation analysis 8. Perform Chi-Square tests

    These outcomes will be achieved through class lectures, reading material, and both book and SPSS homework assignments. Materials will be covered in the following modules.
Basic Concepts

Scales of Measurement (nominal, ordinal, interval, & ratio scales)
Variables (discrete and concrete variables / I.V. & D.V.)
Statistics vs. Population / Random Sampling
Descriptive vs. Inferential Statistics

Displaying Data

Bar Graph & Histogram
Shapes of Distribution (symmetry, skewness)
Grouped Frequency Distribution (SPSS frequency distribution)
Frequency Polygon & Cumulative Frequency Polygon (SPSS frequency polygon)

Measures of Central Tendency (also on SPSS)

The Mode        The Median        The Mean

Measures of Variability (also on SPSS)

The Variance (for population and for sample)
The Standard Deviation (for population and for sample)
Both conceptual and computational formulae for variance and S.D.

Your knowledge of basic concepts, data displays, central tendency, and variability will be measured in Exam one.
The Normal Distribution

The Normal Distribution
The Standard Normal Distribution
Z-score (also on SPSS)

Basic Concepts of Probability

Probability Distributions
Relationship between Z-Score and Probability

Sampling Distribution and Hypothesis Testing

Sampling Distributions of Means (Central Limit Theorem)
Hypothesis Testing (conceptually => z-test)
Probable Limits / One- and Two-Tailed Tests
The Null and Alternative Hypotheses
Type I and Type II Errors
Beta and Power

Your knowledge of distributions, probability, sampling, and hypothesis testing will be measured in Exam two.
One Sample T-test (also on SPSS)

One Sample T-test
Factors that affect the magnitude of t and the decision about H0
Confidence Limits on the Mean

Two Related Samples T-test (also on SPSS)

Student’s t applied to difference scores
Related Samples T-Test

Two Independent Samples T-test (also on SPSS)

Distribution of Differences between Means
Heterogeneity & Homogeneity of Variance
Confidence Limits on µ1 - µ2

Your knowledge of single sample, related samples,  and independent samples t-tests will be measured in Exam three.
One-Way Analysis of Variance (also on SPSS)

Computational ANOVA
Violation of Assumptions

Repeated Measures Analysis of Variance (also on SPSS)

Computational ANOVA
Violation of Assumptions

Your knowledge of one-way ANOVA  and repeated measures ANOVA will be measured in Exam four.

Correlation (also on SPSS)

Classes of Correlation (positive, negative, and zero correlations)
Correlation vs. Causation
The Pearson Product-Moment Correlation Coefficient
Other correlation forms
Testing the Significance of Correlation Coefficients


The Linear Regression Line (computing its equation)
Coefficient of Determination
Standard Error or Estimates

Chi-Square (also on SPSS)

Goodness-of-Fit Test
Test of Independence of Variables

Your knowledge of correlation, and chi-squares will be measured in Exam five.

SCHEDULE: All dates are approximate!

Approximately one chapter each week.
Chapter 1& 2 Introduction & Distributions Chapters 10  t-tests
Chapter 3 Centrality Exam Three
Chapter 4 Variability and Distribution
Exam One Chapter 13 ANOVA
Exam Four
Chapter 5 Distribution, Variance, & Standard deviation
Chapter 6 Normal Distribution (Z scores) Chapter 12 Correlation
Chapter 7 Central Limit Theorem Chapter 16 Chi squares
Chapter 9 Hypothesis Exam 5
Exam Two

Course Requirements:

Grading Scale:

Five exams - 100 points each 500    90%-100% A
Labs(not graded for online class) 100 80%-89.99% B
Homework(not graded for online class) 50 70%-79.99% C
Attendance - (not graded for online class) 50 60%-69.99% D
Total 700 0%-59.99% F

Course Attendance Policy:  

      Attendance is required for this course. Attendance will be taken regularly during class and students who are not present will have 10 points deducted from their attendance score. If you can not attend a class, you will not lose points if you inform the instructor of your expected absence before the absence occurs and provide a student signed excuse for the day of absence.

University Policies:

Academic Integrity

Fairmont State values highly the integrity of its student scholars.  All students and faculty members are urged to share in the responsibility for removing every situation which might permit or encourage academic dishonesty. Cheating in any form, including plagiarism, must be considered a matter of the gravest concern.  Cheating is defined here as the obtaining of information during an examination; the unauthorized use of books, notes, or other sources of information prior to or during an examination; the removal of faculty examination materials; the alteration of documents or records; or actions identifiable as occurring with the intent to defraud or use under false pretense.

Plagiarism is defined here as the submission of the ideas, words (written or oral), or artistic productions of another, falsely represented as one's original effort or without giving due credit.  Students and faculty should examine proper citation forms to avoid inadvertent plagiarism.

Disability Services

Services are available to any student, full or part-time, who has a need because of a [documented] disability.  It is the student’s responsibility to register for services with the coordinator of students with disabilities and to provide any necessary documentation to verify a disability or the need for accommodations.  The Coordinator of Disability Services, Andrea Pammer, is located in Colebank Hall 307.  The office phone is (304) 367-4986. TTY 304-367-4906.   Visit the following website for detailed information.

Students are expected to attend regularly the class and laboratory session of courses in which they are registered. Regular attendance is necessary to the successful completion of a course of study and is an integral part of a student's educational experience.

Each instructor shall make available on the first day of class what the attendance requirements are and what penalties shall be imposed for nonattendance.

Copyright Notice - Material presented in this course may be protected by copyright law.   

Expectations of Students:

Students are expected to be

Present and attentive in class; aware of official university communication via email; Prepared for university life; prepared for class Participating in class and in extra- and co-curricular activities; Polite and respectful to everyone in our academic community.

Visit the following site for detailed information.
Fairmont State’s Core Values:

Scholarship                  Opportunity                  Achievement                  Responsibility

SOAR with Fairmont State

Course Instructor

Profile Photo
Clarence Rohrbaugh
230 Hardway Hall


Course related Institutional Policies