This document includes two activities related to earthquake base isolation. Learners explore earthquake hazards and damage to buildings by constructing model buildings and subjecting the buildings to ground vibration (shaking similar to earthquake vibrations) on a small shake table. Base isolation a powerful tool for earthquake engineering. It is meant to enable a building to survive a potentially devastating seismic impact through a proper initial design or subsequent modifications. The buildings are constructed by two- or three-person learner teams.

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Students can access the textbook as needed to study and work on homework.

Chapter 1. Concepts
Chapter 2. Linear Equations
Chapter 3. Graphing
Chapter 4. Linear Systems
Chapter 5. Polynomial Equations
Chapter 6. Factoring Polynomials
Chapter 7. Rational Expressions
Chapter 8. Radicals
Chapter 9. Quadratic Equations

This free online textbook is a one semester course in basic analysis. These were my lecture notes for teaching Math 444 at the University of Illinois at Urbana-Champaign (UIUC) in fall 2009. The course is a first course in mathematical analysis aimed at students who do not necessarily wish to continue a graduate study in mathematics. A Sample Darboux sums prerequisite for the course is a basic proof course. The course does not cover topics such as metric spaces, which a more advanced course would. It should be possible to use these notes for a beginning of a more advanced course, but further material should be added.

This workbook was created through the efforts of three instructors at Scottsdale Community College in Scottsdale, Arizona. Any individual may download and utilize a digital copy of this workbook for free. The Creative Commons licensing of this text allows others to freely use, modify, or remix any of the information presented here. Contact Donna Gaudet at dgaudet.scc@gmail.com if you are an instructor that wishes to teach with these materials or adapt and edit them for teaching. 238 pages.

In Basic Engineering Data Collection and Analysis, Stephen B. Vardeman and J. Marcus Jobe stress the practical over the theoretical. Step by step, students get real engineering data and scenario examples along with chapter-long case studies that illustrate concepts in realistic, thoroughly detailed situations. This approach encourages students to work through the material by carrying out data collection and analysis projects from problem formulation through the preparation of professional technical reports—just as if they were on the job.

This course is a continuation of MAT087, Basic Mathematics. Topics include signed numbers, decimal numbers, exponential notation, scientific notation, solving and graphing linear equations, an introduction to polynomials, and systems of linear equations and their graphs. Geometrical topics include lines and angles, closed curves and convex polygons, triangles and similarities, and symmetry and proportion in nature and art. Students may complete this course during the first three weeks of the semester by passing the MyMathLab modules. Students will then be eligible to take either MAT 099 Intermediate Algebra, MAT 114-Quantitative Reasoning or MAT 120-Intro to Statistics the following semester. This course does not satisfy degree requirements.

Topics include signed numbers, decimal numbers, exponential notation, scientific notation, solving and graphing linear equations, an introduction to polynomials, and systems of linear equations and their graphs. Geometrical topics include lines and angles, closed curves and convex polygons, triangles and similarities, and symmetry and proportion in nature and art. All course content by Valerie Dietel-Brenneman. Content added to OER Commons by Victoria Vidal.

Topics include signed numbers, decimal numbers, exponential notation, scientific notation, solving and graphing linear equations, an introduction to polynomials, and systems of linear equations and their graphs. Geometrical topics include lines and angles, closed curves and convex polygons, triangles and similarities, and symmetry and proportion in nature and art. Students may complete this course during the first three weeks of the semester by passing the MyMathLab modules. Students will then be eligible to take either MAT 099 Intermediate Algebra, MAT 114-Quantitative Reasoning or MAT 120-Intro to Statistics the following semester. This course does not satisfy degree requirements. Students may complete this course during the first three weeks of the semester by passing the MyOpenMath Acceleration assignments.

Topics include signed numbers, decimal numbers, exponential notation, scientific notation, solving and graphing linear equations, an introduction to polynomials, and systems of linear equations and their graphs. Geometrical topics include lines and angles, closed curves and convex polygons, triangles and similarities, and symmetry and proportion in nature and art. All course content by John McColgan. Content added to OER Commons by Victoria Vidal.

This course is a continuation of MAT087, Basic Mathematics. Topics include signed numbers, decimal numbers, exponential notation, scientific notation, solving and graphing linear equations, an introduction to polynomials, and systems of linear equations and their graphs. Geometrical topics include lines and angles, closed curves and convex polygons, triangles and similarities, and symmetry and proportion in nature and art. Students may complete this course during the first three weeks of the semester by passing the MyMathLab modules. Students will then be eligible to take either MAT 099 Intermediate Algebra, MAT 114-Quantitative Reasoning or MAT 120-Intro to Statistics the following semester. This course does not satisfy degree requirements.

BPCC Open Campus - Math 097: Basic Mathematics is a review of basic mathematics skills. Here's what's covered: -fundamental numeral operations of addition, subtraction, multiplication division of whole numbers, fractions, and decimals -ratio and proportion -percent -systems of measurement -an introduction to geometry NOTE: Open Campus courses are non-credit reviews and tutorials and cannot be used to satisfy requirements in any curriculum at BPCC.

Short Description:
This book provides a brief introduction to some common ideas in the study of probability. At the University of Minnesota, this material is included in a course on College Algebra designed to give students the basic skills to take an introductory Statistics course. The material itself is basic, and should be within the grasp of students who have successfully completed a high school Algebra I course.

Word Count: 1827

ISBN: 978-1-946135-79-7

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Word Count: 19741

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Limited access to subscription-based statistical software poses obstacles when students want to apply the skills they acquired in college. Although students may learn programs like SPSS or Stata while at the university, they often find themselves unable to continue using these programs after graduation, making their acquired skills obsolete. As an open-source software program, R offers a solution to this challenge. It is freely accessible to anyone, including students, after they graduate. Therefore, I decided to write a freely available book for those interested in becoming crime analysts, focusing on learning statistics without delving too deeply into mathematics. Moreover, this book emphasizes practical applications by utilizing R for data analysis, ensuring students can develop relevant skills beyond the university. I hope that students can easily follow the instructions in this book and replicate the same outcomes using the provided data. This practical experience will demonstrate the value of statistics and R, ideally inspiring students to further their learning in these areas.

The first module covers basic whole number concepts and operations.  These are the positive numbers most people recognize when thinking of numbers.  Whole numbers do not include fractions, decimals, and negative numbers, all of which are covered further in other modules.

In the master-equation formalism, a set of differential equations describe the time-evolution of the probability distribution of an ensemble of systems. This can be used, for example, to describe the varied mRNA copy numbers found in individual cells in a population.

The stochastic simulation algorithm (SSA, Kinetic Monte Carlo, Gillespie algorithm) produces an example trajectory for a particular member of a probabilistic ensemble by looping over the following steps. The current state of the system is used to determine the likelihood of each possible chemical reaction in relative comparison to the likelihoods for the other possible reactions, as well as to determine when the next reaction is expected. Pseudo-random numbers are drawn to "roll the dice" to determine exactly when the next reaction will proceed, and which kind of reaction it will happen to be.

This is an Excel spreadsheet and graph that illustrates standard "batch" and Rayleigh decarbonation models and how they can be used to detect fluid infiltration during metamorphism of carbonates. It makes a good lecture demonstration, but with a few modifications can be turned into a laboratory exercise. Key variables are "hotlinked" directly into the batch and Rayleigh models so students can adjust them to get a feel for the influence of different model parameters. The included carbon isotope data are from marbles in the Jervois region, central Australia (Cartwright et al., 1997). Oxygen isotope data are also included in the spreadsheet.

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A series of 63 instructional videos from MATH085 - Pre-Algebra created by Jim Helmer for Bay College.

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