Course Description
Quantitative Reasoning refers to the ability to understand, analyze, and interpret quantitative information, such as data, graphs, and mathematical concepts. It involves the application of mathematical and statistical skills to solve problems, make decisions, and draw logical conclusions. Quantitative Reasoning is an essential skill in many academic and professional domains, such as business, science, engineering, and social sciences, where data-driven decision-making and quantitative analysis are highly valued.
Objectives of Quantitative Reasoning
At the end of this Course, you will be able to:-
Apply Mathematical Concepts: Utilize fundamental mathematical concepts such as arithmetic, algebra, geometry, and statistics to solve practical problems.
Interpret Data: Interpret and analyze data presented in various forms, including tables, charts, graphs, and statistical summaries.
Make Informed Decisions: Make informed decisions based on quantitative analysis, probability assessments, and logical reasoning.
Problem-Solve: Apply quantitative reasoning skills to solve real-world problems across different disciplines and contexts.
Communicate Findings: Effectively communicate findings and conclusions derived from quantitative analysis, both verbally and in written form.
Critically Evaluate Information: Critically evaluate the validity and reliability of quantitative information and sources.
Use Technology: Utilize technology, such as calculators, spreadsheets, and statistical software, to facilitate quantitative analysis and problem-solving.
Develop Quantitative Literacy: Develop a deeper understanding and appreciation for the role of quantitative literacy in personal, professional, and societal contexts.
These objectives collectively aim to equip students with the necessary skills and confidence to engage with quantitative information effectively in their academic pursuits and beyond.
Contents
Section One: Basic Arithmetic
Section Two: Number Sense and Operations
Section Three: Algebraic Reasoning
Section Four: Geometry and Spatial Reasoning
Section Five: Data Analysis and Statistics
