ROCHESTER INSTITUTE OF TECHNOLOGY
School Psychology Program
Course 0527-728-01 Fall 2011
Vincent Pandolfi, Ph.D. Course Outline
Inferential Statistics I
Class Meetings: Wednesday 12:00-1:50pm
Building 1 Room 3338
Instructor: Vincent Pandolfi, Ph.D., Ext. 475-2875
Office Hours: Tuesday 2-4pm & Thursday 10am-12:00pm
Or by appointment
Required Course Textbook:
Hinkle, D.E., Wiersma, W., & Jura, S.G. (2003). Applied statistics for the behavioral sciences
(5th Ed.). Boston: Houghton Mifflin Co.
American Psychological Association (2010). Publication manual of the American Psychological
Association (6th Ed.). Washington, D.C.: Author.
IBM SPSS Statistics (2010). SPSS Base 19.0 user’s guide. Chicago, IL: SPSS, Inc.
This course reviews descriptive and inferential statistics. Basic and advanced conceptual material will be presented to assist students in their understanding of diverse data analytic methods, their appropriate application, and how to interpret statistical analyses. Course content will be taught through lectures, discussion, and applied data analysis exercises. Student mastery of the material will be evaluated through small group discussion of data set analyses, written results of the analyses following APA style, and two exams.
This course aims to develop student competency in the application of descriptive and inferential statistics to school-related problems and original research. This competency will help students: (a) critically evaluate findings reported in scientific papers, (b) evaluate the impact of primary, secondary, and tertiary interventions, and (c) present their own research findings or program evaluation data to relevant stakeholders. Students will develop their understanding of:
- Key concepts and methods in descriptive and inferential statistics;
- Hypothesis testing for multiple independent and dependent samples;
- Statistical software applications;
- How to select appropriate statistical procedures for specific research problems;
- Best practices in interpreting statistical results;
- Best practices in writing reports of findings.
Data Sets: Two take-home data sets will be given during the quarter. Teams of students will select appropriate statistical methods to analyze data to answer specific research questions. Special sessions, held outside of class time, will be arranged with the instructor to review the data sets. Data set answers will be orally defended by the student teams. A written report of findings (i.e., the “Results” section) will be submitted one week after the data set meeting. The written report and all relevant tables must conform to APA style. Grades will be assigned to each individual student based on the quality of the team performance. Each team should be sure that all members contribute equally to the assignment. Concerns about the contributions, or lack thereof, by one or more team members should be addressed directly with them- and, if necessary, brought to the instructor’s attention.
Exams: Two multiple-choice exams will be given. The final exam is not cumulative, but will require knowledge of concepts from the first half of the course.
Each student’s overall grade will be based on a composite of all work during the quarter. Course requirements are weighted as follows:
Data Set I 15%
Data Set II 15%
Exam I 35%
Exam II 35%
Unexcused absences from the data set meeting and missed exams will result in a “0.” No make-up exams will be given. Exceptions to these rules are considered on a case-by-case basis, and final decisions pertaining to grades are at the discretion of the instructor.
As a courtesy, all electronic devices should be turned off or in silent mode. Use of electronic devices for purposes other than for fulfilling course requirements will be directly addressed by the instructor, and can result in a lower participation grade. In the unusual circumstance where a student must immediately address a private matter (e.g., family emergency), he or she may excuse him-/herself and address the matter without penalty.
The main exceptions to this rule are: (a) use of electronic devices for learning or for class participation (e.g., note-taking), and (b) use of electronic devices that represent an accommodation for a disability.
Individuals with Disabilities:
Persons with disabilities requiring specific accommodations should talk privately with the instructor for discussion and planning for individualized needs.
All students will abide by the RIT Academic Honesty Policy (see attached) and the guidelines set forth in the RIT School Psychology Program Student Handbook.
Course Outline- Fall Quarter, 2011
Week Topics Hinkle
9/7 Introduction & Basic Concepts 1-2
9/14 Central Tendency & Variability 3
9/21 Normal Curve 4
9/28 Sampling Distributions 7
10/5 Hypothesis Testing: One-Sample Case 8
10/12 EXAM I Hypothesis Testing:
One-Sample Case Interval Estimation 9
10/19 Hypothesis Testing: Two-Sample Case 11
Data Set #1
10/26 Hypothesis Testing: Two-Sample Case
Results Section Due
11/2 Introduction to Chi-square 21
Data Set #2
11/9 Correlation 5, 20
Results Section Due
11/18 EXAM II