All resources in OpenStax Introductory Business Statistics
Material Type: Textbook
This week we will examine the concept of a function, a fundamental concept underlying all of modern mathematics. You’re undoubtedly already familiar with functions in an intuitive sense: a function is something which, given an input, produces an output. But you’ve probably never seen the formal definition of a function as it relates to set theory, which is what we’ll look at this week.
Material Type: Reading
Introductory survey of quantitative methods (QM), or the application of statistics in the workplace. Examines techniques for gathering, analyzing, and interpreting data in any number of fieldsĺÎĺ from anthropology to hedge fund management.
Material Type: Activity/Lab, Full Course, Homework/Assignment, Reading, Syllabus
Here is the link to the new Passion-Driven Statistics e-book! Github book https://bit.ly/PDSe-book pdf version https://bit.ly/PDSpdf Passion-Driven Statistics is an NSF-funded, multidisciplinary, project-based curriculum that supports students in conducting data-driven research, asking original questions, and communicating methods and results using the language of statistics. The curriculum supports students to work with existing data covering psychology, health, earth science, government, business, education, biology, ecology and more. From existing data, students are able to pose questions of personal interest and then use statistical software (e.g. SAS, R, Python, Stata, SPSS) to answer them. The e-book is presented in pdf format for ease of use across platforms. http://bit.ly/EditPDSe-book For more information, contact Lisa Dierker, email@example.com or check out the Passion-Driven Statistics website at https://passiondrivenstatistics.com/
Material Type: Activity/Lab, Full Course, Homework/Assignment, Lesson Plan, Textbook
This course presents statistical analysis and quantitative tools for applied problem solving and making sound business decisions. Special attention is given to assembling statistical description, sampling, inference, regression, hypothesis testing, forecasting, and decision theory. Course Outcomes: 1. Understand the meaning and use of statistical terms used in todayâ€™s business/economic environment. 2. Collect, organize, summarize, interpret, and present data in tables and charts. 3. Apply descriptive statistical measures to data. 4. Apply probability distributions to model various business and economic processes. 5. Apply statistical inference techniques (including statistical estimation and hypothesis testing) in various business and economic situations. 6. Apply simple linear regression analysis to model various business and economic relationships.
Material Type: Full Course
This sample shell is produced by the California Community Colleges CVC-OEI to support faculty in the use of Open Educational Resources and development of courses aligned to the OEI Course Design Rubric. The shell may be used for online, hybrid, &/or face-to-face classes. The shell is available for all faculty, not just those faculty in the CCC system. The team producing this shell includes Helen Graves, Liezl Madrona, Cyrus Helf, Nicole Woolley & Barbara Illowsky. If you are having challenges importing the shell, here are some steps to take. (1) Create an empty shell in your sandbox. (2) Import the Canvas Commons course into your shell. (3) Adapt the content as you wish. (4) If all else fails, contact your college IT person or Canvas administrator.
Material Type: Full Course
Short Description: This book was created to supplement Math71775 at Conestoga College Word Count: 6754 Included H5P activities: 1 (Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Material Type: Textbook
This collection of spreadsheet-based labs was funded as part of the Digital Learning Research Network (dLRN) made possible by a grant from the Bill and Melinda Gates Foundation. The labs were adapted from the Statistics book, “Introduction to Statistics,” published by OpenStax College. The original labs used graphing calculators and were found within the book after each chapter. These interactive spreadsheet-based labs are effective for online and face-face courses. They may also be used with the book (see Resource: Lab Mapping to Book Chapters) or stand-alone.Authors: Barbara Illowsky PhD, Foothill-De Anza Community College District; Larry Green PhD, Lake Tahoe Community College; James Sullivan, Sierra College; Lena Feinman,College of San Mateo; Cindy Moss, Skyline College; Sharon Bober, Pasadena Community College; Lenore Desilets, De Anza Community College.Lab Mapping to Book ChaptersGrading RubricLabsUnivariarate Data Normal DistributionCentral Limit TheoremHyporhesis Test - Single MeanHyporhesis Test - Single ProportionGoodness of FitLinear Regression
Material Type: Module