Courses tagged with "Web Design" (101)

This course is an introduction to the key ideas and principles of the collection, display, and analysis of data to guide you in making valid and appropriate conclusions about the world.

In this course you will learn about how and why DNA and protein sequences evolve. You will learn the theory behind methods for building and analyzing phylogenetic trees, and get hands-on experience with some widely used software packages.

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.

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…

In this course, you will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge.  You will learn about how statistics and probability work together.  The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.  Statistics formalizes the process of making decisions, and this course is designed to help you use statistical literacy to make better decisions.  Note that this course has applications for the natural sciences, economics, computer science, finance, psychology, sociology, criminology, and many other fields. We read data in articles and reports every day.  After finishing this course, you should be comfortable evaluating an author's use of data.  You will be able to extract information from articles and display that information effectively.  You will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistic…

Learn how advances in geospatial technology and analytical methods have changed how we do everything, and discover how to make maps and analyze geographic patterns using the latest tools.

Let’s make history together - again! 让我们再一次创造历史！

在社会学、心理学、教育学、经济学、管理学、市场学等研究领域的数据分析中，结构方程建模是当前最前沿的统计方法中应用最广、研究最多的一个。它包含了方差分析、回归分析、路径分析和因子分析，弥补了传统回归分析和因子分析的不足，可以分析多因多果的联系、潜变量的关系，还可以处理多水平数据和纵向数据，是非常重要的多元数据分析工具。本课程系统地介绍结构方程模型和LISREL软件的应用，内容包括：结构方程分析（包括验证性因子分析）的基本概念、统计原理、在社会科学研究中的应用、常用模型及其LISREL程序、结果的解释和模型评价。学员应具备基本的统计知识（如：标准差、t-检验、相关系数），理解回归分析和因子分析的概念。 注：本课程配套教材为《结构方程模型及其应用》（以LISREL软件为例）。

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.

This cross-disciplinary course deals with the undetermined, the unpredictable- or what appears to be such. Learn about the usefulness of randomness in communication and computation, the intrinsic randomness of quantum phenomena, the unpredictability of the weather, and the implications of the neural activity of the brain on our "free will".

Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.

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.

Learn to frame and address health-related questions using modern biostatistics ideas and methods.

Education is increasingly occurring online or in educational software, resulting in an explosion of data that can be used to improve educational effectiveness and support basic research on learning. In this course, you will learn how and when to use key methods for educational data mining and learning analytics on this data.

This course provides an introduction to various classes of derivative securities and we will learn how to price them using "risk-neutral pricing". In the follow-up to this course (FE & RM Part II) we will consider portfolio optimization, risk management and more advanced examples of derivatives pricing including, for example, real options and energy derivatives.

This course follows on from FE & RM Part I. We will consider portfolio optimization, risk management and some advanced examples of derivatives pricing that draw from structured credit, real options and energy derivatives. We will also cast a critical eye on how financial models are used in practice.

The Coursera course, Data Analysis and Statistical Inference has been revised and is now offered as part of Coursera Specialization “Statistics with R”. This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

How astronomy really works - an overview of the technology that astronomers use to collect and measure light from the universe, and how it is used in practice to make scientific discoveries.

Use of available (mainly web-based) programs for analyzing biological data. This is an introductory course with a strong emphasis on hands-on methods. Some theory is introduced, but the main focus is on using extant bioinformatics tools to analyze data and generate biological hypotheses.

Learn both theory and application for basic methods that have been invented either for developing new concepts – principal components or clusters, or for finding interesting correlations – regression and classification. This is preceded by a thorough analysis of 1D and 2D data.