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Graduate Course Proposal Form Submission Detail - NGR7843

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Current Status: Approved, Permanent Archive - 2006-12-05
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  1. Department and Contact Information

    Tracking Number Date & Time Submitted
    1750 2006-06-13
     
    Department College Budget Account Number
    Nursing NR 6201-000-0
     
    Contact Person Phone Email
    Jason Beckstead 9747667 jbeckste@health.usf.edu

  2. Course Information

    Prefix Number Full Title
    NGR 7843 Statistical Methods in Nursing Research III

    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

    Credit Hours Section Type Grading Option
    3 C - Class Lecture (Primarily) R - Regular
     
    Abbreviated Title (30 characters maximum)
    Stats Methd in Nur Resh III
     
    Course Online? Percentage Online
    -

    Prerequisites

    NGR 7842

    Corequisites

    Course Description

    Focus on advanced multivariate statistical methods in nursing research; emphasizing multiple regression and correlational analysis.


  3. Justification

    A. 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.

    B. 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.

    C. 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.

    D. 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


  4. Other Course Information

    A. 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.

    B. 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.

    C. 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

    D. Textbooks

    Tabachnick, B.G. & Fidell, L.S. (2001). Using multivariate statistics. 4th ed. Allyn & Bacon:

    Needham Heights, MA. ---or latest edition---

    E. Course Readings, Online Resources, and Other Purchases

    F. Student Expectations/Requirements and Grading Policy

    G. Assignments, Exams and Tests

    H. Attendance Policy

    I. Policy on Make-up Work

    J. Program This Course Supports


  5. Course Concurrence Information



- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.