Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

These materials are meant as a supplement for teachers and learners who are using the OpenStax Introductory Statistics textbook by Illowsky and Dean. These materials also incorporate the use of other technologies (R and Excel) in an open statistics course for students and instructors who wish to use technologies other than the TI-83/84 graphing calcuator.

As a supplement to the OpenStax textbook, we have also created lesson summaries for our OER course. Attached are some instructor created notes on the following topics.Introduction to StatisticsSampling MethodsBias in SamplingOrganizing Data using Frequency Distributions and HistogramsMeasures of CenterMeasures of Dispersion and Empirical RuleMeasures of Position, Fences and Outliers5-Number Summary and Boxplots

This activity reinforces learning about levels of measurement and frequency distributions in an intro level Social Science Statistics course. Students identify something up from their life, collect data for their variable, assess its level of measurement and make a frequency distribution. 

Aimed at statistics beginners, this learning object describes, and gives examples of, the four levels of measurement of data: nominal, ordinal, interval and ratio.

This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.

Students typically find linear regression analysis of data sets in a biology classroom challenging. These activities could be used in a Biology, Chemistry, Mathematics, or Statistics course. The collection provides student activity files with Excel instructions and Instructor Activity files with Excel instructions and solutions to problems.

Students will be able to perform linear regression analysis, find correlation coefficient, create a scatter plot and find the r-square using MS Excel 365. Students will be able to interpret data sets, describe the relationship between biological variables, and predict the value of an output variable based on the input of an predictor variable.

The 15.821 and 15.822 Sequence
Marketing research may be divided into methods that emphasize understanding “the customer” and methods that emphasize understanding “the market.” This course (15.821) deals with the customer and emphasizes qualitative methods (interviews, focus groups, Voice of the Customer, composing questions for a survey). The companion course (15.822) deals with the market and emphasizes quantitative methods (sampling, survey execution, quantitative data interpretation, conjoint analysis, factor analysis).
The methods covered in 15.821 are often used in the “front-end” of market research project, whose second-stage is a quantitative survey. The quality of information gathered in the second-stage is greatly enhanced in this way.
15.821 is designed for the nonspecialist, e.g., someone planning a career in general management, product or project management, R&D, advertising, or entrepreneurship. 15.822 teaches analytical techniques that are standard in consulting or marketing research, and is ideally suited for students planning careers in those fields.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Researchers have developed a new way to interpret risk and prognosis in patients with diffuse large B-cell lymphoma Using a novel statistical method, they’ve calculated the loss in life expectancy for those affected by the cancer This value represents the difference in remaining life years between patients and the general population Unlike 5-year survival, loss in life expectancy offers a straightforward way to estimate the impact of cancer over a person’s entire lifespan The researchers estimated trends in life-years lost due to cancer for recently diagnosed patients and for two-year survivors before and after rituximab became available and found that patients diagnosed in the rituximab era experienced fewer years lost than those diagnosed in the early 2000s But the results also revealed that young high-risk patients with primary refractory disease and early relapse still experience significantly reduced life expectancies highlighting one of the most important groups still in need of new ap.."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Overview of statistical methods used in collecting, tabulating, analyzing, and presenting data. Topics include frequency distributions, measures of central tendency, elementary probability, statistical inference, ANOVA, and statistical software.

This supplement is designed for MTH 243 at Portland Community College and is used in conjunction with OpenStax Statistics: https://openstax.org/details/introductory-statistics

This supplement is designed for MTH 244 at Portland Community College and is used in conjunction with OpenStax Statistics: https://openstax.org/details/introductory-statistics

This supplement is designed for MTH 244 at Portland Community College and is used in conjunction with OpenStax Statistics: https://openstax.org/details/introductory-statistics

This course presents a challenging multi-dimensional perspective on the causes of human disease and mortality. The course focuses on analyses of major causes of mortality in the US since 1900: cancer, cardiovascular and cerebrovascular diseases, diabetes, and infectious diseases. Students create analytical models to derive estimates for historically variant population risk factors and physiological rate parameters, and conduct analyses of familial data to separately estimate inherited and environmental risks. The course evaluates the basic population genetics of dominant, recessive and non-deleterious inherited risk factors.

This course introduces you to behavioral science theories, methods, and tools and provides opportunities to use and apply them to problems you will encounter in your work and career. The course material will begin with an overview of work and organizations in modern industrial society, and then examine individual behavior, move to behavior in groups or teams, and finally discuss organizations as a whole. It is expected that at the end of the course you will: (a) know something about managerial psychology, (b) know how to learn more, (c) understand the behavioral research process, and (d) develop skills in presenting your ideas in oral and written reports.