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12 Mar

Applied Multivariate Data Analysis Techniques AssignmentTutorOnline | Good Grade Guarantee!

Seminar in Applied Multivariate Data Analysis Techniques
Course Overview
This three-credit seminar course is designed for graduate students to enhance their applied multivariate data analysis knowledge and skills.

Enrollees completing this course will be able to:
Select multivariate statistical techniques appropriate for specific research situations.
Assess whether the statistical assumptions for various multivariate procedures have been met.
Conduct multivariate data analysis using SPSS software.
Interpret SPSS output for various multivariate techniques.
Write results from various multivariate techniques for their theses/dissertations/journal articles/reports.
Interpret multivariate analyses techniques used in top-tier journals, reports, and other publications
Assignments and Grading
The student work will be assessed objectively, and students are required to complete the following exams and assignments to determine final grades.
Final Paper: You will submit a final individual paper, which will take the format of a journal article in the leading journal of your profession. For this assignment, first, you will submit a one-page overview, i.e., concept note of your final paper which will be
scored on a 50-point scale, later you will submit the first draft of final paper for a grade  of 100 points, and finally, you will submit the final paper for a grade of 250 points. This final paper assignment in total counts for 400 points (40%) of your course grade. A detailed description of the final paper assignment will be distributed in the class. See the due dates for the final paper assignments in the course schedule.

There is no required textbook. The readings for class are distributed to students one week prior to the class.
Students may wish to purchase the following book as a supplemental reference for the course:
Field, A. (2018). Discovering statistics using SPSS. London, UK: Sage publications. Mertler, C. A., & Vannatta, R. A. (2010). Advanced and multivariate statistical methods:
Practical application and interpretation. Glendale, CA: Routledge.
Tabachnick, B. G. & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston: Allyn & Bacon.

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The instructor will use the Statistical Package for Social Sciences (SPSS) to carry out analysis for various data analysis techniques. Students can access the SPSS for free in their classroom, i.e., 202 Chambers Building. Students are also encouraged to obtain a copy of SPSS statistical software for his or her personal computers. Students can rent the SPSS for six months at $58.99 from http://www.onthehub.com/spss/.

Computer printouts will be provided for each of the seminar topics. We will interpret the information on those printouts.
You will “run” the SPSS computer program. I will provide a copy of the class data set to “run” computer programs on your own using the class data file.

The very useful website from UCLA with examples, syntax, and annotated outputs https://stats.idre.ucla.edu/spss/
Using SPSS to Understand Research and Data Analysis http://wwwstage.valpo.edu/other/dabook/home.htm
Statsoft Electronic Statistics Textbook http://www.statsoft.com/Textbook

As a matter of mutual courtesy, please let the instructor know when you are going to be late, when you are going to miss class, or if you need to leave early. Please try to do any of these as little as possible. Students are expected to be present for all classes since much material will be covered only once in class. Attendance will not be checked or graded, but you are responsible for the content of all classes, including issues raised in the spontaneous class discussions. If you must miss a class, please request notes from your classmates.

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Disability Statement: Penn State welcomes students with disabilities into the University’s educational programs. Every Penn State campus has an office for students with disabilities. The Office for Disability Services (ODS) Web site provides contact information for every Penn State campus: http://equity.psu.edu/. For further information, please visit the Office for Disability Services Web site: http://equity.psu.edu/ods.
In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation: http://equity.psu.edu/ods/guidelines. If the documentation supports your request for
reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.
Academic Integrity Statement: Penn State and the College of Agricultural Sciences take violations of academic integrity very seriously. Faculty, alumni, staff and fellow students expect each student to uphold the University’s standards of academic integrity both in and outside of the classroom.
Academic integrity is the pursuit of scholarly activity in an open, honest and responsible manner. Academic integrity is a basic guiding principle for all academic activity at The Pennsylvania State University, and all members of the University community are expected to act in accordance with this principle. Consistent with this expectation, students should act with personal integrity, respect other students’ dignity, rights, and property, and help create and maintain an environment in which all can succeed through the fruits of their efforts. Academic integrity includes a commitment not to engage in or tolerate acts of falsification, plagiarism, misrepresentation or deception. Such acts of dishonesty violate the fundamental ethical principles of the University community and compromise the worth of work completed by others (see Faculty Senate Policy 49‐20 and
 G‐9 Procedures) https://studentaffairs.psu.edu/support-safety-conduct/student- conduct/code-conduct ).
Academic Integrity Guidelines for the College of Agricultural Sciences can be found at http://agsci.psu.edu/students/resources/academic-integrity

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