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

This textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.

150 REAL GRE Quantitative Reasoning questions--direct from the test maker! The best way to prepare for the Quantitative Reasoning measure of the GRE revised General Test is with real GRE test questions--and that is what you will find in this unique guide! Specially created for you by ETS, it offers 150 actual Quantitative Reasoning questions with complete explanations. Plus, this guide includes a review of math topics likely to appear on the Quantitative Reasoning measure. Only ETS can show you exactly what to expect on the test. So for in-depth practice and accurate test preparation for the Quantitative Reasoning measure, this guide is your best choice! Look inside to find: Real GRE Quantitative Reasoning test questions arranged by content and question type--to help you build your test-taking skills. Plus, mixed practice sets. Answers and explanations for every question! GRE Math Review covering math topics you need to know for the test. ETS's own test-taking strategies: Valuable hints and tips to help you do your best on the test. Official information on the GRE Quantitative Reasoning measure: The facts about the test content, structure, scoring, and more--straight from ETS.

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.

Making Sense of Numbers teaches students the skills they need to be both consumers and producers of quantitative research: able to read about, collect, calculate, and communicate numeric information for both everyday tasks and school or work assignments. The text teaches how to avoid making common errors of reasoning, calculation, or interpretation by introducing a systematic approach to working with numbers, showing students how to figure out what a particular number means. The text also demonstrates why it is important to apply a healthy dose of skepticism to the numbers we all encounter, so that we can understand how those numbers can (and cannot) be interpreted in their real-world context. Jane E. Miller uses annotated examples on a wide variety of topics to illustrate how to use new terms, concepts, and approaches to working with numbers. End-of-chapter engagement activities designed based on Miller’s three decades of teaching experience can be used in class or as homework assignments, with some for students to do individually and others intended for group discussion. The book is ideally suited for a range of courses, including quantitative reasoning, research methods, basic statistics, data analysis, and communicating quantitative information. An instructor website for the book includes a test bank, editable PowerPoint slides, and tables and figures from the book.

Mathematics for Social Justice: Focusing on Quantitative Reasoning and Statistics offers a collection of resources for mathematics faculty interested in incorporating questions of social justice into their classrooms. The book comprises seventeen classroom-tested modules featuring ready-to-use activities and investigations for college mathematics and statistics courses. The modules empower students to study issues of social justice and to see the power and limitations of mathematics in real-world contexts of deep concern. The primary focus is on classroom activities where students can ask their own questions, find and analyze real data, apply mathematical ideas themselves, and draw their own conclusions. Module topics in the book focus on technical content that could support courses in quantitative reasoning or introductory statistics. Social themes include electoral issues, environmental justice, equity/inequity, human rights, and racial justice, including topics such as gentrification, partisan gerrymandering, policing, and more. The volume editors are leaders of the national movement to include social justice material in mathematics teaching and jointly edited the earlier AMS-MAA volume, Mathematics for Social Justice: Resources for the College Classroom. Gizem Karaali is Professor of Mathematics at Pomona College. She is a past chair of the Special Interest Group of the MAA on Quantitative Literacy (SIGMAA-QL). She is one of the founding editors of The Journal of Humanistic Mathematics, senior editor of Numeracy, and an associate editor for The Mathematical Intelligencer; she also serves on the editorial board of the MAA's Classroom Resource Materials series. Lily Khadjavi is Professor and Chair of Mathematics at Loyola Marymount University and is a past co-chair of the Infinite Possibilities Conference. In 2020 she was appointed by the California State Attorney General to the Racial and Identity Profiling Act Board, which works with the California Department of Justice. She currently serves on the editorial board of the MAA's Spectrum series and the Human Resources Advisory Committee for the Mathematical Sciences Research Institute in Berkeley.