Covers whole numbers, fractions, decimals, percents, ratios and proportions, measurement, and integers. Geometry and statistics are integrated throughout the text rather than covered in independent sections. The textbook does not include exercises. Instead, a collection of handouts/worksheets is available, as well as online homework.
Designed to meet scope and sequence requirements for a one-semester prealgebra course. The book’s organization makes it easy to adapt to a variety of course syllabi. The text introduces the fundamental concepts of algebra while addressing the needs of students with diverse backgrounds and learning styles.
Provides a comprehensive exploration of algebraic principles and meets scope and sequence requirements for a typical introductory algebra course. The modular approach and richness of content ensure that the book meets the needs of a variety of courses.
An introductory text for a college algebra survey course. The material is presented at a level intended to prepare students for Calculus while also giving them relevant mathematical skills that can be used in other classes.
This text comprises a three–text series on Calculus. The 1st part covers material taught in many “Calc 1” courses: limits, derivatives, and the basics of integration. The 2nd text covers material often taught in “Calc 2:” integration and its applications, along with an introduction to sequences, series and Taylor Polynomials. The 3rd text covers topics common in “Calc 3” or “multivariable calc:” parametric equations, polar coordinates, vector–valued functions, and functions of more than one variable.
An introductory textbook aimed at college-level sophomores and juniors. Typically students will have taken calculus, but it is not a prerequisite. The book begins with systems of linear equations, then covers matrix algebra, before taking up finite-dimensional vector spaces in full generality.
Presents an introduction to the fascinating subject of linear algebra. As the title suggests, this text is designed as a first course in linear algebra for students who have a reasonable understanding of basic algebra. Major topics of linear algebra are presented in detail, with proofs of important theorems provided.
This textbook covers topics such as taxes, gross earnings, product prices, currency exchange; loans, lines of credit, mortgages, leases, savings bonds, and other financial tools. It also discusses how to execute smart monetary decisions both personally and for their business.
Follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory.
Introduces students to the discipline of statistics as a science of understanding and analyzing data. Students learn how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
This textbook is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it.
This text is designed for an introductory probability course taken by sophomores, juniors, and seniors in mathematics, the physical and social sciences, engineering, and computer science. It presents a thorough treatment of probability ideas and techniques necessary for an understanding of the subject.
An introduction to Python programming for beginners. It starts with basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression.
The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. The single most important skill for a computer scientist is problem solving. As it turns out, the process of learning to program is an excellent opportunity to practice problem solving skills using Python programming.