In this module, students reconnect with and deepen their understanding of statistics and probability concepts first introduced in Grades 6, 7, and 8. Students develop a set of tools for understanding and interpreting variability in data, and begin to make more informed decisions from data. They work with data distributions of various shapes, centers, and spreads. Students build on their experience with bivariate quantitative data from Grade 8. This module sets the stage for more extensive work with sampling and inference in later grades.

Find the rest of the EngageNY Mathematics resources at https://archive.org/details/engageny-mathematics.

Description:After playing this game, students will explain the functions and role of intermediaries and defend their importance.

Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. 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.

Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. 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 custom textbook collection has been modified by R. Bloom for her classes at De Anza College; the homework content for the custom collection is now contained in a separate homework collection.

This is a custom collection (by R. Bloom) of homework and review problems to accompany Collaborative Statistics textbook custom collection by R. Bloom. Content is derived from Collaborative Statistics written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook by S. Dean and B. Illowsky was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. 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 custom version of their collection has been modified by R. Bloom for her classes at De Anza College.

The primary objective is to teach students to do rigorous, explicit, customer-based marketing analysis which is most appropriate for new ventures. Explicit analysis of customers and potential customers, using available data, together with explicit and sensible additional assumptions about customer needs and behavior. Additional course objectives are to teach students about: (a) ways to implement marketing strategies when resources are very limited, and (b) common deficiencies in marketing by entrepreneurial organizations. From course home page: Course Description Educational Objective This course clarifies key marketing concepts, methods, and strategic issues relevant for start-up and early-stage entrepreneurs. At this course, there are two major questions: Marketing Question: What and how am I selling to whom? New Venture Question: How do I best leverage my limited marketing recourses? Specifically, this course is designed to give students a broad and deep understanding of such topics as: What are major strategic constraints and issues confronted by entrepreneurs today? How can one identify and evaluate marketing opportunities? How do entrepreneurs achieve competitive advantages given limited marketing resources? What major marketing/sales tools are most useful in an entrepreneurial setting? Because there is no universal marketing solution applicable to all entrepreneurial ventures, this course is designed to help students develop a flexible way of thinking about marketing problems in general. Career Focus This course is aimed at students who plan to start a new venture or take a job as a marketing professional in an early-stage business.

All of us have felt sick at some point in our lives. Many times, we find ourselves asking, "What is the quickest way that I can start to feel better?" During this two-lesson unit, students study that question and determine which form of medicine delivery (pill, liquid, injection/shot) offers the fastest relief. This challenge question serves as a real-world context for learning all about flow rates. Students study how long various prescription methods take to introduce chemicals into our blood streams, as well as use flow rate to determine how increasing a person's heart rate can theoretically make medicines work more quickly. Students are introduced to engineering devices that simulate what occurs during the distribution of antibiotic cells in the body.

Introduction to the sources of technological innovation, economics of innovation, protection of innovation rights, communication of technical information, capturing benefit from innovation, organizing to manage the innovation process, cooperation in the innovation process, new ventures. 15.351 is a full-term subject with greater detail on technology strategy and on product development and implementation. 15.352 is a half-term subject. Students cannot receive credit for both subjects.

Provides an understanding of the distribution of organic carbon (OC) in marine sediments from a global and molecular-level perspective. Surveys the mineralization and preservation of OC in the water column and within anoxic and oxic marine sediments. Topics include: OC composition, reactivity and budgets within, and fluxes through, major reservoirs; microbial recycling pathways for OC; models for OC degradation and preservation; role of anoxia in OC burial; relationships between dissolved and particulate (sinking and suspended) OC; methods for characterization of sedimentary organic matter; application of biological markers as tools in oceanography. Both structural and isotopic aspects are covered.

An introduction to pharmacology. Topics include mechanisms of drug action, dose-response relations, pharmacokinetics, drug delivery systems, drug metabolism, toxicity of pharmacological agents, drug interactions, and substance abuse. Selected agents and classes of agents examined in detail.

" This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice."

Student worksheet to calculate the topics of stock turnover and open to buy

Application-oriented introduction to systems optimization focusing on understanding system tradeoffs. Introduces modeling methodology (linear, network, integer, nonlinear programming, and heuristics), modeling tools (sensitivity and postoptimality analysis), software, and applications in production planning and scheduling, inventory planning, supply network optimization, project scheduling, telecommunications, facility sizing and capacity expansion, product development, yield management, electronic trading, and finance.

Video explains the elements of operations management and their importance to business success

The Wisconsin Department of Natural Resources uses a variety of tools and techniques to monitor wildlife, and to produce population estimates to better inform management decisions. Population estimates are used to look at long term trends, as well as setting harvest limits during hunting seasons for potentially vulnerable species. There are two count methods for generating population information: sample counts and total counts. In total counts, every individual of an intended geographic area is counted. For sample counts, a smaller fraction of individuals are counted and the data is used to interpolate population information for the entire geographic area. In this activity, you will create a model for these two different count methods and explore the advantages and disadvantages to both approaches.

(Nota: Esta es una traducción de un recurso educativo abierto creado por el Departamento de Educación del Estado de Nueva York (NYSED) como parte del proyecto "EngageNY" en 2013. Aunque el recurso real fue traducido por personas, la siguiente descripción se tradujo del inglés original usando Google Translate para ayudar a los usuarios potenciales a decidir si se adapta a sus necesidades y puede contener errores gramaticales o lingüísticos. La descripción original en inglés también se proporciona a continuación.)

En este módulo, los estudiantes reconectan y profundizan su comprensión de las estadísticas y los conceptos de probabilidad introducidos por primera vez en los grados 6, 7 y 8. Los estudiantes desarrollan un conjunto de herramientas para comprender e interpretar la variabilidad en los datos, y comienzan a tomar decisiones más informadas de los datos . Trabajan con distribuciones de datos de varias formas, centros y diferenciales. Los estudiantes se basan en su experiencia con datos cuantitativos bivariados del grado 8. Este módulo prepara el escenario para un trabajo más extenso con muestreo e inferencia en calificaciones posteriores.

Encuentre el resto de los recursos matemáticos de Engageny en https://archive.org/details/engageny-mathematics.

English Description:
In this module, students reconnect with and deepen their understanding of statistics and probability concepts first introduced in Grades 6, 7, and 8. Students develop a set of tools for understanding and interpreting variability in data, and begin to make more informed decisions from data. They work with data distributions of various shapes, centers, and spreads. Students build on their experience with bivariate quantitative data from Grade 8. This module sets the stage for more extensive work with sampling and inference in later grades.

Find the rest of the EngageNY Mathematics resources at https://archive.org/details/engageny-mathematics.