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Quantitative Reasoning-ii (Evidence-Based Practice) - (QRE212) (DPT): Course Outline

Quantitative research refers to any research based on something that can be accurately and precisely measured and will include studies that have numerical data. Quantitative data are expressed numerically and analyzed statistically. The data are collected

Course Content

CONTENT
1. Logic, logical and critical reasoning
• Introduction and importance of logic
• Inductive, deductive and abductive approaches of reasoning
• Propositions, arguments  logical connectives, truth tables
• Logical fallacies
• Vann Diagrams
• Predicates and quantifies
• Quantitative reasoning exercises using logical reasoning concepts and techniques
2. Mathematical modeling and analyses
• Introduction to deterministic models
• Use of linear functions for modeling in real-world situations
• Modeling with the system of linear equations and their solutions
• Elementary introduction to derivatives in mathematical modeling
• Linear and exponential growth and decay models
• Quantitative reasoning exercises using mathematical modeling
3. Statistical modeling and Analyses
• Introduction to probabilistic models
• Bivariate analysis, scatter plots
• Simple linear regression model and correction analysis
• Basics of estimation and confidence interval
• Testing of hypothesis (z-test, t-test)
• Statistical inference in decision making
• Quantitative reasoning exercise using statistical modeling

Course Objectives

COURSE LEARNING OUTCOMES :
By the end of this course, students shall have
1. Understanding of logic and logical reasoning
2. Understanding of basic quantitative modeling and analyses
3. Logical reasoning skills and abilities to apply them to solve quantitative problems and evaluate
arguments
4. Ability to critically evaluate quantitative information to make evidence based decisions through
appropriate computational tools