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Graduate Course Proposal Form Submission Detail - NGR7843
Tracking Number - 1750
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Current Status:
Approved, Permanent Archive - 2006-12-05
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Detail Information
- Date & Time Submitted: 2006-06-13
- Department: Nursing
- College: NR
- Budget Account Number: 6201-000-0
- Contact Person: Jason Beckstead
- Phone: 9747667
- Email: jbeckste@health.usf.edu
- Prefix: NGR
- Number: 7843
- Full Title: Statistical Methods in Nursing Research III
- Credit Hours: 3
- Section Type: C -
Class Lecture (Primarily)
- Is the course title variable?: N
- Is a permit required for registration?: N
- Are the credit hours variable?: N
- Is this course repeatable?:
- If repeatable, how many times?: 0
- Abbreviated Title (30 characters maximum): Stats Methd in Nur Resh III
- Course Online?: -
- Percentage Online:
- Grading Option:
R - Regular
- Prerequisites: NGR 7842
- Corequisites:
- Course Description: Focus on advanced multivariate statistical methods in nursing research; emphasizing multiple regression and correlational analysis.
- Please briefly explain why it is necessary and/or desirable to add this course: Students in the PhD program in Nursing require additional coursework in statistical methods, particularly in multivariate methods.
- What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? This course is required for all doctoral students in Nursing and is the final course in a series of three.
- Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? This course has never been offered in the College.
- What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) Doctoral degree with a strong background in research methods and statistical analysis is required
- Objectives: Objectives:
1) Provide the researcher, as distinct from the statistician, with a survey of several of the more
commonly used multivariate procedures, including multiple regression, path analysis, and factor
analysis;
2) Introduce a conceptual framework of measurement and structural modeling with which to apply
and interpret multivariate statistics in the research process;
3) Illustrate how to conduct multivariate analyses using SPSS and LISREL programs.
- Learning Outcomes: Objectives:
1) Provide the researcher, as distinct from the statistician, with a survey of several of the more
commonly used multivariate procedures, including multiple regression, path analysis, and factor
analysis;
2) Introduce a conceptual framework of measurement and structural modeling with which to apply
and interpret multivariate statistics in the research process;
3) Illustrate how to conduct multivariate analyses using SPSS and LISREL programs.
- Major Topics: The Multivariate Perspective & Introduction
Simple Linear Regression
Multiple Regression w/ 2 Independent Variables
Multiple Regression: General Method w/ Matrix Algebra
Multiple Regression using Categorical Predictors
Trend Analysis: Linear & Curvilinear Regression
Introduction to Factor Analytic Methods
Exploratory Factor Analysis
Technical Aspects of Factor Analysis
Introduction to Path Analysis
Path Analysis using SPSS
Introduction to Structural Equation Modeling
Path Analysis using LISREL
Confirmatory Factor Analysis using LISREL
- Textbooks: Tabachnick, B.G. & Fidell, L.S. (2001). Using multivariate statistics. 4th ed. Allyn & Bacon:
Needham Heights, MA. ---or latest edition---
- Course Readings, Online Resources, and Other Purchases:
- Student Expectations/Requirements and Grading Policy:
- Assignments, Exams and Tests:
- Attendance Policy:
- Policy on Make-up Work:
- Program This Course Supports:
- Course Concurrence Information:
- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.