Testing
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The course covers basic concepts of biomedical engineering and their connection with the spectrum of human activity. It serves as an introduction to the fundamental science and engineering on which biomedical engineering is based. Case studies of drugs and medical products illustrate the product development-product testing cycle, patent protection, and FDA approval. It is designed for science and non-science majors.
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Programming Methodology is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software...more
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Refresh: Permute Code, Tree of Recursive Calls, Live Demo: Testing with Different Cases, Eliminating Duplicates, Subsets, Subset Strategy, Subset Code, Tree of RecursiveCalls: Subset, Exhaustive Recursion, Recursive Backtracking, Turning Recursive Permute to Backtracking, Permute -> Anagram Finder Code, Decision Problems: 8 Queens, Extension to N Queens
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Kelley talks about how the observation phase is the most overlooked part of the development process. Kelley hires social scientists to watch people complete tasks instead of asking them usability questions. He prefers to see them as customers instead of users and strongly believes that customer satisfaction comes with understanding their values. He gives examples of how his team will observe a customer in their usual environment instead...more
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I never had a technology company, says Hawkins. He believes that products come out of product marketing people who really love and understand products. He asks his employees to use competitor products to learn something from them. The focus should be on what people want and what they need, rather than only on technology.To build a successful product one has to innovate continuously, focusing on what people do and not what they say. And if...more
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Product decisions can be based on the company politics. But one cannot argue with facts and stats, and this is the basis, says Marissa Mayer, Google's Vice President of Search Products & User Experience, by which the company bases its decisions. Google's approach is the take the guesswork out of product design, from functionality to shades of color, and they believe in the science of well-monitored and frequent A/B testing.
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Investors Mike Maples and Ron Conway explain their job like this: They help all lights turn green for the fast-moving car of the Internet start-up. In addition to cutting a check, these angel investors explain the panoramic view of what a good investor offers, including bringing in the right talent and business sensibilities, and building and testing product prototypes.
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Yahoo! President Sue Decker explains the search engine's testing of Google tools to help close the gap between user search and moneymaking ad clicks. She explains that the partnership was part of the due diligence necessary to benchmark Yahoo!'s own capability to turn search engine users into those who buy from well-targeted on-site ads.
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Reedy talks about how the eBay team came to the rescue in September 2001. The team was given only three days to launch The Auction for America, which required 20 hours alone for coding and additional time for testing. One hundred people worked on this over the weekend and they had the product one hour before the deadline. No one said we can't do this, she says. The teams had to collaborate and work together to get this done.
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Rodan discusses the importance of market research while building and testing a product. She also elaborates on how market research was conducted to help develop a good product.
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Winblad advises entrepreneurs to boil down their business plan and tell everyone in the company the top five assumptions for success. As time goes on, turn the assumptions into facts, she says. Understand the core assumptions you are making and keep reevaluating them, she adds.
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Statistical Estimation, Maximum Likelihood Estimation, Examples, Logistic Regression, (Binary) Hypothesis Testing, Scalarization, Experiment Design, D-Optimal Design
