The Best Mathematics Books 2024

1. Carson Dellosa Singapore Math Level 5A Math Practice Workbook (128 pages)

Welcome to Singapore Math––the leading math program in the world! This workbook features math practice and activities for sixth grade students based on the Singapore Math method. Level A is designed for the first semester and Level B is for the second. An introduction at the front of each book explains Singapore Math and its common problem types. Each unit has learning objectives, which clearly define the skills to be learned in that section, and an answer key with step-by-step worked out solutions that help students see how to work the problems. This book is perfect for students familiar with Singapore Math and for those who just need extra math practice! Directly correlated to Singapore Math textbooks, this comprehensive practice series allows learners to practice various types of math problems while developing their thinking and analytical skills. Learning objectives and unit assessments are included to ensure that students obtain a thorough understanding of each concept. Perfect as a supplement to classroom work or as a homeschool resource, these workbooks will boost confidence in problem-solving and critical-thinking skills.

Features math practice and activities based on the Singapore Math method Allows learners to practice various types of math problems while developing their thinking and analytical skills Learning objectives and assessments are provided Workbooks will boost confidence in learner’s problem-solving and critical-thinking skills 128 pages

2. Statistics: An Introduction Using R (Paperback) by Michael J Crawley

9780470022986. New condition. Trade paperback. Language: English. Pages: 342. Trade paperback (US). Glued binding. 342 p. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the authora s previous best--selling title Statistical Computing. aeo Features step--by--step instructions that assume no mathematics, statistics or programming background, helping the non--statistician to fully understand the methodology. aeo Uses a series of realistic examples, developing step--wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. aeo The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. aeo Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. aeo Includes numerous worked examples and exercises within each chapter. aeo Accompanied by a website featuring worked examples, data sets, exercises and solutions: ... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology -- but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

ISBN: 9780470022986 Condition: New Trade paperback Language: English Pages: 342 Trade paperback (US). Glued binding. 342 p. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the authora s previous best--selling title Statistical Computing. aeo Features step--by--step instructions that assume no mathematics, statistics or programming background, helping the non--statistician to fully understand the methodology. aeo Uses a series of realistic examples, developing step--wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. aeo The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. aeo Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. aeo Includes numerous worked examples and exercises within each chapter. aeo Accompanied by a website featuring worked examples, data sets, exercises and solutions: ... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology -- but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

3. Number Theory (Paperback) by George E Andrews

9780486682525. New condition. Trade paperback. Revised ed. Language: English. Pages: 288. Trade paperback (US). Glued binding. 288 p. Dover Books on Mathematics. Undergraduate text uses combinatorial approach to accommodate both math majors and liberal arts students. Covers the basics of number theory, offers an outstanding introduction to partitions, plus chapters on multiplicativity-divisibility, quadratic congruences, additivity, and more.

Although mathematics majors are usually conversant with number theory by the time they have completed a course in abstract algebra, other undergraduates, especially those in education and the liberal arts, often need a more basic introduction to the topic. In this book the author solves the problem of maintaining the interest of students at both levels by offering a combinatorial approach to elementary number theory. In studying number theory from such a perspective, mathematics majors are spared repetition and provided with new insights, while other students benefit from the consequent simplicity of the proofs for many theorems. Among the topics covered in this accessible, carefully designed introduction are multiplicativity-divisibility, including the fundamental theorem of arithmetic, combinatorial and computational number theory, congruences, arithmetic functions, primitive roots and prime numbers. Later chapters offer lucid treatments of quadratic congruences, additivity (including partition theory) and geometric number theory. Of particular importance in this text is the author's emphasis on the value of numerical examples in number theory and the role of computers in obtaining such examples. Exercises provide opportunities for constructing numerical tables with or without a computer. Students can then derive conjectures from such numerical tables, after which relevant theorems will seem natural and well-motivated.