1). Summarize and describe the distribution of a categorical variable in context. …
1). Summarize and describe the distribution of a categorical variable in context. 2). Generate and interpret several different graphical displays of the distribution of a quantitative variable (histogram, stemplot, boxplot). 3). Summarize and describe the distribution of a quantitative variable in context: a) describe the overall pattern, b) describe striking deviations from the pattern. 4). Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts. 5). Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context. 5). Apply the standard deviation rule to the special case of distributions having the "normal" shape.
Activity Sheets, tightly aligned with the OpenStax College Algebra text, and designed …
Activity Sheets, tightly aligned with the OpenStax College Algebra text, and designed for use in class as part of an active lecture. During the 2020-2021 pandemic, the activity sheets were used successfully in both group and individual settings in hybrid and fully online learning environmentsThis resource includes activities formatted both as accessible Word documents, for ease of use under the CC-BY 4.0 license, and in pdf form to preserve historically the intended appearance on the page.These activity sheets align tightly with the OpenStax College Algebra textbook and an available MyOpenMath Course called the College Algebra Western MD Consortium (MOST), an inter-institutional effort comprised of mathematics faculty, instructional designers, and libriarians from Frostburg State University, Allegany College of Maryland, and Garrett College.
This course provides an introduction to mathematical modeling of computational problems. It …
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
This book is meant to be a textbook for a standard one-semester …
This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students. Our motivation for writing it is twofold: 1.) to provide a low-cost alternative to many existing popular textbooks on the market; and 2.) to provide a quality textbook on the subject with a focus on the core material of the course in a balanced presentation.
A course containing formative and summative assessments, guided reading notes, and in-class …
A course containing formative and summative assessments, guided reading notes, and in-class active-learning activities tightly aligned with OpenStax College Algebra with trigonometric topics from the OpenStax Algebra with Trigonometry textbook. Ancillary materials are available for download from OER Commons (See Note to Instructors within course) include active-learning worksheets and guided reading note assignments.Topics covered support transferability of College Algebra from two-year to four-year institutions within the University System of Maryland, including verbal, tabular, graphical, and algebraic representations of the functions of college algebra (linear, power/polynomial, rational, exponential, logarithmic, and trigonometric), operations and characteristics of functions, transformations, and systems of linear and nonlinear functions. Prerequisite topics and a review of intermediate algebra are included with assessment but without ancillary materials. This course is suitable for flipped classrooms as well as active-learning environments or may be used without the activity sheets for hybrid or online delivery. It has been used successfully with instructor-created lecture videos (not included) for intense 3 to 6 week online sessions.Provided by the Western Maryland OER Collaboration, an interinstitutional team supported by the Maryland Open Source Textbook Initiative (M.O.S.T.).
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