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MOOC
basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Social surveys -- Methodology Social sciences -- Research -- Methodology
- Resource Type:
- MOOC
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Courseware
Statistics is the science that turns data into information and information into knowledge. This class covers applied statistical methodology from an analysis-of-data viewpoint. Topics covered include frequency distributions; measures of location; mean, median, mode; measures of dispersion; variance; graphic presentation; elementary probability; populations and samples; sampling distributions; one sample univariate inference problems, and two sample problems; categorical data; regression and correlation; and analysis of variance. Use of computers in data analysis is also explored.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Statistics
- Resource Type:
- Courseware
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MOOC
over the basic elements of designing and evaluating questionnaires.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Social surveys Social sciences -- Research Questionnaires -- Methodology
- Resource Type:
- MOOC
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e-book
I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning. Chapters 2–10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word “recursion”1 does not appear in the book at all. In chapters 1 and 11–16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data. The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one chooses not to become a professional programmer.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
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MOOC
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Video
alterative pain control
- Subjects:
- Nursing and Rehabilitation Sciences
- Keywords:
- Pain -- Treatment
- Resource Type:
- Video
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Courseware
The primary goal of this course is to promote an evidence-based approach to advanced nursing practice. Evidenced-based research findings for nursing practice will be evaluated in terms of racial, ethnic, and socioeconomic relevance. An understanding of the research process, applicable theories, organizational dynamics, and leadership functions are applied to design and process of implementing research in health care settings.
- Subjects:
- Statistics and Research Methods and Nursing
- Keywords:
- Nursing -- Research -- Methodology Evidence-based nursing
- Resource Type:
- Courseware
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Courseware
This course introduces the student to global health concepts and the network of organizations working to advance health care internationally. Emphasis for this course is on the global burden of disease and determinates of health. It will provide the student with a broad introduction to programs, systems and policies affecting global health. Students will explore facets of the global health care delivery system, health care economics and the political process and its impact on the health of individuals and populations.
- Subjects:
- Public Health
- Keywords:
- Medical economics Public health administration World health Children -- Health hygiene
- Resource Type:
- Courseware
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MOOC
Most professions these days require more than general intelligence. They require in addition the ability to collect, analyze and think about data. Personal life is enriched when these same skills are applied to problems in everyday life involving judgment and choice. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research. Concepts are defined briefly and breezily and then applied to many examples drawn from business, the media and everyday life.
What kinds of things will you learn? Why it’s usually a mistake to interview people for a job. Why it’s highly unlikely that, if your first meal in a new restaurant is excellent, you will find the next meal to be as good. Why economists regularly walk out of movies and leave restaurant food uneaten. Why getting your picture on the cover of Sports Illustrated usually means your next season is going to be a disappointment. Why you might not have a disease even though you’ve tested positive for it. Why you’re never going to know how coffee affects you unless you conduct an experiment in which you flip a coin to determine whether you will have coffee on a given day. Why it might be a mistake to use an office in a building you own as opposed to having your office in someone else’s building. Why you should never keep a stock that’s going down in hopes that it will go back up and prevent you from losing any of your initial investment. Why it is that a great deal of health information presented in the media is misinformation.
- Keywords:
- Reasoning Problem solving Critical thinking Decision making
- Resource Type:
- MOOC
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Courseware
Math 679 is a graduate level mathematics course whose purpose is to prove Mazur's theorem (link is external). Mazur's theorem is a well-known and important result, however it is not often taught in classroom settings. The course is divided into three parts: elliptic curves and abelian varieties, moduli of elliptic curves, and proof of Mazur’s theorem.
- Keywords:
- Abelian varieties Curves Algebraic Curves Elliptic
- Resource Type:
- Courseware
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