Marketing research may be divided into methods that emphasize understanding “the customer” and methods that emphasize understanding “the market.” This course (15.822) deals with the market. The companion course (15.821) deals with the customer.
The course will teach you how to write, conduct and analyze a marketing research survey. The emphasis will be on discovering market structure and segmentation, but you can pursue other project applications.
A major objective of the course is to give you some “hands-on” exposure to analysis techniques that are widely used in consulting and marketing research factor analysis, perceptual mapping, conjoint, and cluster analysis). These techniques used to be considered advanced but now involve just a few keystrokes on most stat software packages.
The course assumes familiarity with basic probability, statistics, and multiple linear regression.

An examination of a variety of mathematical concepts which focus on solving problems, interpreting data, and applications. This course includes topics such as tables, graphs, basic statistics, geometric measures, and consumer mathematics. This course fulfills the BCC mathematics requirement ONLY for the Criminal Justice, Fire Science, and Human Services programs.

Systems engineering is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and reliability improvement while considering the complete problem including operations, performance, test, manufacturing, cost, and schedule. This course emphasizes the links of systems engineering to fundamentals of decision theory, statistics, and optimization. The course also introduces the most current, commercially successful techniques for systems engineering.

In order to promote students’ conceptual understanding and learning experience in introductory statistics, a technology task, which focuses on the probability distribution in which means are defined, was created using TinkerPlots, an exploratory data analysis and modeling software. The targeted audiences range from senior high school grade levels to college freshmen who are starting their introductory course in statistics. Students will be guided to explore and discover the movement behaviors of means of a set of numbers randomly generated from a fixed range of values characterized by a predetermined probability distribution. The cognitive, mathematical, technological and pedagogical natures of the task, as well as its association with the statistics education framework based on the Guidelines for Assessment and Instruction in Statistics Education (GAISE) by the American Statistical Association, will be elaborated. A brief discussion on what cognitive design principles this task satisfies will also be provided at the end.

Think Stats is an introduction to Probability and Statistics for Python programmers.

*Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
*If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.

As part of our NSF-funded passion-driven statistics project, we have just started to share more widely our “translation code” aimed at supporting folks in learning code-based software and in moving more easily between them.  The pdf includes all of the basic syntax for managing, displaying and analyzing data, translated across SAS, R, Python, Stata and SPSS. http://bit.ly/PDSTranslationCodeFor more information about our full project and access to all faculty resources, email Kristin.Flaming@gmail.com

A study by David Baker and colleagues reveals poor quality of reporting in pre-clinical animal research and a failure of journals to implement the ARRIVE guidelines. There is growing concern that poor experimental design and lack of transparent reporting contribute to the frequent failure of pre-clinical animal studies to translate into treatments for human disease. In 2010, the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were introduced to help improve reporting standards. They were published in PLOS Biology and endorsed by funding agencies and publishers and their journals, including PLOS, Nature research journals, and other top-tier journals. Yet our analysis of papers published in PLOS and Nature journals indicates that there has been very little improvement in reporting standards since then. This suggests that authors, referees, and editors generally are ignoring guidelines, and the editorial endorsement is yet to be effectively implemented.

The following are some common methods of data collection in statistical studies that involve people.

This course gives an introduction to probability and statistics, with emphasis on engineering applications. Course topics include events and their probability, the total probability and Bayes’ theorems, discrete and continuous random variables and vectors, uncertainty propagation and conditional analysis. Second-moment representation of uncertainty, random sampling, estimation of distribution parameters (method of moments, maximum likelihood, Bayesian estimation), and simple and multiple linear regression. Concepts illustrated with examples from various areas of engineering and everyday life.

Authors: Erin M. Buchanan, Tabetha Hopke, Simon DonaldsonEducational use: Use these materials to teach an undergraduate statistics course with a primary social science focus.Abstract: Want to teach an undergraduate statistics course using open source materials? You have come to the right place! A complete set of how-to guides for JASP, learning objectives, and pre-made course materials for you to use in your class.Audience: Educators, Students who need extra how-to helpLevel: IntroductoryPrerequisites: None

Activity introduces students to the concept of sampling distributions and point estimates, and to how the accuracy of point estimates are affected by sample size.

Students build on their existing air quality knowledge and a description of a data set to each develop a hypothesis around how and why air pollutants vary on a daily and seasonal basis. Then they are guided by a worksheet through an Excel-based analysis of the data. This includes entering formulas to calculate statistics and creating plots of the data. As students complete each phase of the analysis, reflection questions guide their understanding of what new information the analysis reveals. At activity end, students evaluate their original hypotheses and “put all of the pieces together.” The activity includes one carbon dioxide worksheet/data set and one ozone worksheet/data set; providing students and/or instructors with a content option. The activity also serves as a good standalone introduction to using Excel.

The Uniform Crime Reporting (UCR) Program generates reliable statistics for use in law enforcement. It also provides information for students of criminal justice, researchers, the media, and the public. The program has been providing crime statistics since 1930.

The UCR Program includes data from more than 18,000 city, university and college, county, state, tribal, and federal law enforcement agencies. Agencies participate voluntarily and submit their crime data either through a state UCR program or directly to the FBI's UCR Program.

Students will examine ways declining bee population can impact day to day life, by considering how the cost of honey and pollination has been affected society Students will create real-world problems that relate to statistics on the declining bee population.

Students will examine ways declining bee population can impact day to day life, by considering how the cost of honey and pollination has been affected society Students will create real-world problems that relate to statistics on the declining bee population.

Students will examine ways declining bee population can impact day to day life, by considering how the cost of honey and pollination has been affected society Students will create real-world problems that relate to statistics on the declining bee population.

This is an interdisciplinary lesson that incorporates tools learned in Algebra about analyzing data representations to apply to historical and literary purposes.

Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.

Increasingly, public agencies are adopting models of self-assessment in which administrative data are used to guide and then continuously evaluate the implementation of programs and policies. In California, public child welfare agencies track performance outcomes spanning a range of child safety, permanency, and well-being domains, as dictated by federal and state mandates. This curriculum has been designed to provide Title IV-E and others students interested in public child welfare systems with an overview of the state’s Child Welfare Outcomes and Accountability System. Students will be provided with hands-on opportunities to become experienced and “statistically literate” users of aggregate, public child welfare data from the state’s administrative child welfare system, attending to the often missing link between data/research and practice. This curriculum is organized into five teaching modules, providing instructors with student learning activities, PowerPoint slide presentations, and other materials to support graduate IV-E students in the development of practical data analysis skills. Materials focus on publicly available data hosted through the Child Welfare Indicators Project at the University of California at Berkeley, a long-standing agency/university data partnership: http://cssr.berkeley.edu/ucb_childwelfare. CalSWEC funding for the development of this curriculum was provided to the Child Welfare Performance Indicators Project. Modules were developed to support instructors of both first- and second-year MSW research courses. Module objectives include: (a) to support student (and instructor) understanding of California's child welfare system performance goals and progress to date; (b) to develop students who have highly desirable (and practical) data analysis skills, including the ability to intelligibly distill and present numerical findings; and (c) to prepare a cohort of IV-E MSW students equipped to adopt leadership roles in county child welfare agencies, bringing with them an appreciation for how data can be used to improve practice and inform policies. Putnam-Hornstein, E., Needell, B., Lery, B., King, B., & Weigmann, W. (2013).

Students will utilize an applet to further expand their knowledge of confidence intervals.