The field of statistics is continuing to grow more relevant than ever due to the complexities of our modern world. Statisticians compute data to provide information that can guide and enable corporations and governments to make better decisions. The first lesson in the course explores the various ways data and statistics are used. You will realize that statistics is not just about analyzing data. It is about the whole process of using scientific methods to answer questions and make decisions.
When data is gathered, it is often translated into numbers for further processing. We will, therefore, discuss the two main statistical methods of numerical analysis. Following any analysis, it is important to organize and present data to make your arguments clear; you will understand how to effectively and correctly communicate information using graphs, especially the bar graphs, which depict qualitative data that have been summarized in a frequency distribution.
A good hypothesis translates a problem statement or a research question into a form that is more amenable to testing. You will discover the nature of a hypothesis and the process of hypothesis testing. We then focus on methods used to gather data for testing. Explore interviewing skills and data-gathering tools such as surveys and questionnaires. Data experts are needed in various sectors such as business, education, and healthcare; if this is your area of interest, sign up and start learning today!
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MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathe…
A curated collection of videos featuring top experts in artificial intelligence.
-Learn more and enroll in the program: https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program Recent advancements in generative AI are reshaping industries, pushing technological boundaries, and revolutionizing creative processes. In this fast-changing landscape…
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Delve into the exciting world of Artificial Intelligence with insights and research from the world's top experts. This playlist offers a comprehensive journey, from foundational machine learning con…
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabili…
