Introduction To Quantitative Reasoning

Introduction to QR, Quantitative Reasoning and Discrete Mathematics was designed for the introductory college student who may not have fully understood mathematical concepts in secondary schools. With a focus on applications, this book is divided into small digestible pieces with lots of examples illustrating a variety of topics. Use the whole book for a two semester sequence, or pick and choose topics to make a single semester course. The most basic of algebra topics are reintroduced, with an emphasis on learning how to translate scenarios into problems that can be solved or modeled with linear functions. Scientific notation and significant figures are applied to problems involving unit conversion, including examples with the Consumer Price Index. The basics of personal finance are explained, including interest, loans, mortgages, and taxes. Statistical topics are introduced to give the students the ability to look critically at the myriad of numerical sound bites tossed out in today’s social media. Combinatorics and probability topics are introduced in a way to be accessible to students seeing the material for the first time. Logic and graph theory are used to solve some traditional types of games and puzzles. Applications are connected to issues in modern Christianity with references to 18th century philosopher Emanuel Swedenborg, including why Intelligent Design does not act as proof of God, and how random chance and Divine Providence work together. Each chapter ends with a project related to the chapter, often involving spreadsheet programs or website data collection. About the Author Neil Simonetti, PhD, Professor of Mathematics and Computer Science at Bryn Athyn College, has been teaching Mathematics, Computer Science and Operations Research courses for almost 20 years. He is committed to showing students who are afraid of mathematics that the basics of this subject do not have to be difficult and confusing. This work results from discovering what these students need in mathematics to succeed in business, science, and social science courses.

An engaging introduction to data science that emphasizes critical thinking over statistical techniques An introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives. Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel. Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking. An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields Introduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity Uses real-world examples and data from a wide variety of subjects Includes practice questions and data exercises

While Applying Social Statistics is 'about' social statistics and includes all of the topics generally covered in similar texts, it is first and foremost a book about how sociologists use statistics. Its emphasis is on statistical reasoning in sociology and on showing how these principles can be applied to numerous problems in a wide variety of contexts; to answer effectively the question 'what's it for.' A main learning objective is to help students understand how and why social statistics is used. Yet, Weinstein's style and substance recognize that it is of equal-or even greater-importance that they begin to learn how to apply these principles and techniques themselves.

"The purpose of this Quantitative Reasoning (QR) course is to provide a comprehensive overview of the quantitative skills required to cope with the practical demands of daily life, as well as preparing students for a deeper understanding of information presented in mathematical terms. Critical thinking and problem solving are an emphasis. The application of quantitative skills to decision making, requiring reasoning from evidence, enhances your students' personal, civic, and business lives. These reasoning capabilities are based upon the ability to communicate with numbers effectively, so developing quantitative literacy is a key focus"--