Students in Independent Studies engage in-depth exploration in an independent learning experience. Students, in consultation with the course faculty member, choose a specific topic of their interest (project, paper, and......) to investigate, develop a Learning Contract, outlining learning objectives, a learning action plan, teaching strategies and an evaluation plan. The nature and amount of time and guidance to be provided by the faculty member are also determined.

This course introduces the beginnings of nursing to the student in terms of the history of nursing, its nature and roles. The course has been prepared to provide the student with basic information, ethical and legal aspects of nursing care. Emphasis will be placed on critical thinking and the nursing process as a basis for the practice.

This course introduces the student to clinical decision-making in nursing. The nursing process is presented, with the focus on making nursing diagnoses and identifying outcome criteria. The social, legal, ethical and cultural context of decision making in nursing is explored. Research is introduced as a method of inquiry and as a foundation for evidence based clinical decisions. Clinical decision-making to promote patient adaptation is emphasized. Students have the opportunity to practice decision making skills in simulated and actual patient settings

The goal of this course is to introduce students to the fundamentals of economic theory and the analysis of economic activities at the micro level. The course applies economic analysis to understand the behavior of households and firms. Furthermore, the course introduces the various market structures to students (perfect competition, monopoly, imperfect competition, etc.)

Financial markets and others generate vast amounts of data on asset returns, their volatility, and other financial variables in long and high-frequency time series. The ability to analyze market behavior requires knowledge of the properties of time series and appropriate estimation methods. Since the early 1980s techniques for analyzing time series, which exhibit auto-regression, have yielded important studies of financial markets, increasing our knowledge of financial variables’ volatility.