Courses tagged with "Statistics and Data Analysis" (99)
Programming-oriented course on effectively using modern computers to solve scientific computing problems arising in the physical/engineering sciences and other fields. Provides an introduction to efficient serial and parallel computing using Fortran 90, OpenMP, MPI, and Python, and software development tools such as version control, Makefiles, and debugging.
In this course you will learn the basics of the life-cycle assessment (LCA) method for holistic environmental analysis of products, technologies, and systems. LCA sheds light on the environmental implications of the consumption and behavioral choices we all make on a daily basis.
Learn about inferential statistics, and how they are used and misused in the social and behavioral sciences. Learn how to critically evaluate the use of inferential statistics in published research and how to generate these statistics yourself, using freely available statistical software.
Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data. #uwdatasci
This course exposes students to the logic of statistical reasoning and its application in the quantitative social sciences. It is meant as a thorough but accessible introduction to the topics of descriptive statistics, probability theory, and statistical inference with hands-on exercises.
If you invest in financial markets, you may want to predict the price of a stock in six months from now on the basis of company performance measures and other economic factors. As a college student, you may be interested in knowing the dependence of the mean starting salary of a college graduate, based on your GPA. These are just some examples that highlight how statistics are used in our modern society. To figure out the desired information for each example, you need data to analyze. The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding in complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information. This course will begin with a brief overview of the discipline of stat…
This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
How can we know if the differences in wages between men and women are caused by discrimination or differences in background characteristics? In this course we look at causal effects as opposed to spurious relationships. We will discuss how they can be identified in the social sciences using quantitative data, and describe how this can help us understand social mechanisms.
Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.
Everyone in education has questions – Practical Learning Analytics is about answering them. To be practical, we’ll focus on data every university records; to keep things interesting, we’ll examine questions raised by many audiences; to ensure impact, we’ll provide realistic data and example code.
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