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UT Arlington PSYC 5405 - Syllabus

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1PSYC 5405 Advanced Statistics I Fall 2009 Instructor: Angela Liegey Dougall, PhD Office Location: 523 Life Science Office Telephone Number: 817-272-0531 Email address: [email protected] (do NOT email me through WebCT) Course Website: Please go to WebCT at Office Hours: Tuesday & Thursday 2:00-3:00 PM and by appointment Time and Place of Class Meetings: Lecture: 420 Life Science; Tuesday & Thursday 12:30-1:50 PM Lab: 04 University Hall; Monday 4:00-6:50 PM Lab Teaching Assistant: Coordinator: Jason Popan Wen Cheng Office Location 537 Life Science 405 Life Science Email Address: [email protected] [email protected] Office Hours: Monday 12:00 - 2:00 PM and by appointment Wednesday 1:00-2:00 PM and by appointment Description of Course Content: PSYC5405- ADVANCED STATISTICS I 4 hours credit The course offers an in-depth practical and conceptual approach to fundamental descriptive and inferential statistics used in psychological research. Student Learning Outcomes: This course consists of learning a variety of procedures commonly used to test hypotheses in psychological research, learning to examine and analyze the data accordingly, and learning to communicate the research results to the scientific community. Specific learning outcomes are listed below. 1. Learn how to create a database and how to properly code and screen data and present the results by using SPSS or another statistical software package for data management and database creation and by conducting appropriate data screening procedures and writing sections describing data screening for assignments, take-home exams, and the final project. 2. Learn how to determine and describe the strength of association and direction of relationships between two or more variables by identifying and computing (both by hand and with a statistical package) appropriate statistical tests, such as chi-square statistics, correlation coefficients, and linear regression models, and by writing Data Analysis and Results sections.23. Learn how to examine and present significant mean differences between and within groups by identifying and computing (both by hand and with a statistical package) appropriate statistical tests, such as t-tests and analysis of variance models (ANOVA), and by writing Data Analysis and/or Results sections. 4. Learn how to write professional papers by composing drafts of one complete paper and many drafts of Data Analysis and Results Sections each using the knowledge gained about APA writing style and the content of each of these sections. Requirements: One (1) lab section is available. You must be registered in lecture (PSYC 5405-001) and the lab section (PSYC 5405-002) concurrently. Please see the lab schedule for further information. Required texts and resources (bring texts to lecture and lab): - Howell, D. C. (2010). Statistical methods for psychology (7th ed.). Belmont, CA: Wadsworth. (ISBN: 978-0-495-59784-1) - Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Thousand Oaks, CA: Sage. (ISBN: 978-1-84787-907-3) - American Psychological Association (2009). Publication manual of the American Psychological Association (6th edition). Washington, D.C.: APA. (ISBN: 1-4338-0561-8) - UT Austin SPSS Online Tutorial available at . - Reserved readings will be available in the Science Education and Career Center in LS106. Required supplies: - A calculator will be needed. - Access to a computer with statistical software. Computers are available in the OIT Labs. The following labs have computers on which PASW/SPSS is installed: Business Building, Fine Arts Building, Ransom Hall, and University Hall. Computers with statistical software (PASW/SPSS & SAS) are also available in the Graduate Reading Room (LS544B) and statistical software is available for purchase through the University of Texas at Arlington. PASW/SPSS will be used in the lecture and lab but students are able to use another statistical software program if they choose. Recommended (optional) resources: Assignments and exams: In addition to in-class exercises, other exercises and assignments will be scheduled throughout the term. Homework assignments will be and worth 100 points. Participation in lecture and lab will also be worth 100 points. Two cumulative take-home exams will be given and will be worth 100 points each. See the course schedule for exam dates. A final project will be due on November 30, 2009 and will be worth 200 points. The final project will be a complete manuscript that will consist of using the statistical analyses learned in this course to test hypotheses generated by the student using a database identified by the student. Approval of hypotheses, data analyses, and data sets must be secured prior to submitting the final project.3Attendance: Regular attendance at lecture and lab is expected and counts toward the participation grade. Make-up work: Make-up and/or late assignments and exams will be granted only for University-approved, documented absences. Grading: You will receive one course grade for your combined performance in the lecture and laboratory. You will have a chance to earn 600 points total. There will be two take-home exams worth 100 points each and a final project worth 200 points. Additionally, lecture and lab participation will be worth 100 points and homework assignments will be worth 100 points. Final course grades will be calculated by adding participation, homework, exam and final project points together, dividing by 600, and assigning final letter grades as follows: Letter Grade Percentage of Points Points required A 89.5-100.0% 537-600 B 79.5-89.4% 477-536.4 C 69.5-79.4% 417-476.4 D 59.5%-69.4% 357-416.4 F 0%-59.4% 0-356.4 Grade Grievance Policy: The University Grade Grievance Policy will be followed. (See Grade Grievance Policy in the Graduate School Regulations and Information.) Drop Policy: The University Drop Policy will be followed. (See Drop Policy in the Graduate School Regulations and Information.) Americans With Disabilities Act: The University of Texas at Arlington is on record as being committed to both the spirit and letter of federal equal opportunity legislation; reference Public Law

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