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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.
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, supplemental reading lists, and links to online videos, interactive materials, and other resources. ÿ Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets.ÿ
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.
HSPT Practice Questions are the simplest way to prepare for the HSPT. Practice is an essential part of preparing for a test and improving a test taker's chance of success. The best way to practice taking a test is by going through lots of practice test questions. If someone has never taken a practice test, then they are unprepared for the types of questions and answer choices that they will encounter on the official test. There is a tremendous advantage to someone taking the test that is already familiar with the questions and answer choices. Another advantage of taking practice tests is that you can assess your performance and see if you need to study and practice more, or if you're already prepared enough to achieve success on your test day. If you do well on the practice test, then you know you're prepared. If you struggle on the practice test, then you know you may still have more work to do to get prepared. Taking lots of practice tests helps ensure that you are not surprised or disappointed on your test day. Our HSPT Practice Questions give you the opportunity to test your knowledge on a set of questions. You can know everything that is going to be covered on the test and it will not do you any good on test day if you have not had a chance to practice. Repetition is a key to success and using practice test questions allows you to reinforce your strengths and improve your weaknesses. Detailed answer explanations are also included for each question. It may sound obvious, but you have to know which questions you missed (and more importantly why you missed them) to be able to avoid making the same mistakes again when you take the real test. That's why our HSPT Practice Questions include answer keys with detailed answer explanations. These in-depth answer explanations will allow you to better understand any questions that were difficult for you or that you needed more help to understand.
Part of an integrated math/science curriculum developed at New York University for non-science majors. Covers how to measure things in the real world, growth and decay phenomena, scaling transformations, introductory probability and statistics. Includes readings.
One CD-ROM disc in pocket.
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--