The following files accompany this module: 06_BDIs_CDIs.xlsx 06_Exercises.xls 06_GEOMEAN_index.xlsx 06_SubwaySystem_Stations.xlsx 06_UnweightedPriceIndex 06_WeightedIndex.xlsx

The following files accompany this module 07_Gombaud_Solution.xls 07_FACT_COMBIN_PERMUT.xlsx 07_Exercises.xlsx

The following files accompany this module: 08_Examples.xlsx 08_Exercises.xlsx BinomialTable.xlsx Hypergeometric_Calculator.xlsx PoissonTable.xlxs

The following files accompany this module: 09_Examples.xlsx 09_Exercises.xlsx 09_NormalCurve_ShadedArea.xlsx 09_SolvingForX.xlsx z-Values_AreaBetweenMean&X.xlsx

This course covers relations and functions, specifically, linear, polynomial, exponential, logarithmic, and rational functions. Additionally, sections on conics, systems of equations and matrices and sequences are also available.

College Algebra 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. College Algebra offers a wealth of examples with detailed, conceptual explanations, building a strong foundation in the material before asking students to apply what they've learned.

Note: this resource now links to the second edition, released in 2021. This record is in maintained in OER Commons to allow users to see endorsements, reviews, etc... for the 1st edition.

Combinatorics is an upper-level introductory course in enumeration, graph theory, and design theory.

his book is an introduction to combinatorial mathematics, also known as combinatorics. The book focuses especially but not exclusively on the part of combinatorics that mathematicians refer to as “counting.” The book consists almost entirely of problems. Some of the problems are designed to lead you to think about a concept, others are designed to help you figure out a concept and state a theorem about it, while still others ask you to prove the theorem. Other problems give you a chance to use a theorem you have proved. From time to time there is a discussion that pulls together some of the things you have learned or introduces a new idea for you to work with. Many of the problems are designed to build up your intuition for how combinatorial mathematics works. There are problems that some people will solve quickly, and there are problems that will take days of thought for everyone. Probably the best way to use this book is to work on a problem until you feel you are not making progress and then go on to the next one. Think about the problem you couldn’t get as you do other things. The next chance you get, discuss the problem you are stymied on with other members of the class. Often you will all feel you’ve hit dead ends, but when you begin comparing notes and listening carefully to each other, you will see more than one approach to the problem and be able to make some progress. In fact, after comparing notes you may realize that there is more than one way to interpret the problem. In this case your first step should be to think together about what the problem is actually asking you to do. You may have learned in school that for every problem you are given, there is a method that has already been taught to you, and you are supposed to figure out which method applies and apply it. That is not the case here. Based on some simplified examples, you will discover the method for yourself. Later on, you may recognize a pattern that suggests you should try to use this method again.

Using highly interactive learning design, this Concepts in Statistics course provides students with a strong understanding of fundamental principles that guide the study of statistical inference. Drawing from Open Learning Initiative (OLI) source content, this course’s simulations and lab-style synthesis activities invite hands-on exploration of statistical concepts. Students learn to summarize data graphically and numerically; examine relationships among quantitative data; understand the role of probability and probability distributions; link probability to statistical inference; and conduct foundational statistical calculations and analyses.

A Cool, Brisk Walk Through Discrete Mathematics, an innovative and non-traditional approach to learning Discrete Math, is available for low cost from Blurb or via free download.

This open resources textbook contains 10 Units that describe and explain the main concepts in statistical analysis of psychological data (managing data, measures of central tendency, measures of spread, correlations, simple linear regression). In addition to conceptual descriptions and explanations of the basic analyses for descriptive statistics, this textbook also explains how to conduct those analyses with common statistical software (Excel) and open-source free software (R). This book is directed to undergraduates studying basic statistics, especially basic statistics in psychological research.

This is a textbook for teaching data science using the Python programming language at a general first year undergraduate level.

This is a textbook for teaching data science using the R programming language at a general first year undergraduate level.

Discrete mathematics is applied in many areas including the physical, engineering, and increasingly, the social sciences. This online textbook, written by mathematics and information technology professors, is aimed at students of information technology, computer science, and applied mathematics. The focus is on applying discrete math techniques from the two broad component areas of discrete math, namely combinatorics or enumerative techniques, and graph theory.

Compiled to support a course on teaching math and science in Early Childhood Education. Chapters include: Early Learning; Math & Science Connections; Theory & Teacher Effectiveness; Special Needs; Standards & Assessment; Lesson Planning; Centers & Environment; Teaching Science Content; Teaching Math Content; and Hands-on Learning.

This book is not intended for budding mathematicians. It was created for a math program in which most of the students in upper-level math classes are planning to become secondary school teachers. For such students, conventional abstract algebra texts are practically incomprehensible, both in style and in content. Faced with this situation, we decided to create a book that our students could actually read for themselves. In this way we have been able to dedicate class time to problem-solving and personal interaction rather than rehashing the same material in lecture format.

This text is appropriate for a course that introduces undergraduates to proofs. The material includes elementary symbolic logic, logical arguments, basic set theory, functions and relations, the real number system, and an introduction to cardinality. The text is intended to be readable for sophomore and better freshmen majoring in mathematics.

The source files for the text can be found at https://github.com/RPMillspaugh/SetTheory

Elements of Abstract and Linear Algebra is a book written by Dr. Edwin Connell, a professor emeritus in the math department at the University of Miami. Published in December 2001, it can be obtained free of charge from this Web site. Dr. Connell even encourages printing and distributing the book as an inexpensive resource for college students. The text is divided into sections that can be downloaded separately or as a whole. There are many theorems, proofs, and exercises throughout the book that illustrate the underlying concepts. The book is offered in four formats; so, most computers should be able to view it with no problems.