Online courses directory (11)
This course will introduce you to business statistics, or the application of statistics in the workplace. Statistics is a course in the methods for gathering, analyzing, and interpreting data. If you have taken a statistics course in the past, you may find some of the topics in this course familiar. You can apply statistics to any number of fields from anthropology to hedge fund management because many of us best interpret data when it is presented in an organized fashion (as it is with statistics). You can analyze data in any number of forms. Summary statistics, for example, provide an overview of a data set, such as the average score on an exam. However, the average does not always tell the entire story; for example, if the average score is 80, it may be because half of the students received 100s and the other half received 60s. This would present a much different story than if everyone in the class had received an 80, which demonstrates consistency. Statistics provides more than simple averages. In t…
This course will introduce you to entrepreneurship and business planning. By way of introduction, the word entrepreneur originates from the French word entreprendre, meaning to undertake. Today, we define an entrepreneur as an owner or manager of a business enterprise who attempts to make profits by starting and growing his or her business. In earnest, entrepreneurs are a diverse group of risk-takers who share the same goal of cultivating ideas and developing them into viable business opportunities. Take a quick look at the statistics below to get a sense for some of the (potentially surprising) qualities that have been attributed to entrepreneurs. According to a recent report by the US Census, every day approximately 2,356 Americans are becoming entrepreneurs by starting new businesses. According to 2006 report from Northeastern University’s School of Technological Entrepreneurship, 62% of entrepreneurs in the US claim innate drive as the number one motivator in starting their business. According t…
Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. The field of data mining has evolved from the disciplines of statistics and artificial intelligence.
This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. We will survey applications and provide an opportunity for hands-on experimentation with algorithms for data mining using easy-to- use software and cases.
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…
Math for Economists will help you assemble a toolkit of skills and techniques to solve fundamental problems in both macroeconomics and microeconomics. The material covers both precalculus and calculus concepts and should help you identify the best approach to solving problems. For example, an economist may be called upon to determine the right mix allocation of capital to a production process. The tools in this course will help you evaluate the options and select from the best alternatives. Advanced courses in economics typically utilize mathematical techniques beyond basic calculus; so, gaining practice in fundamental skills can serve as a good basis for further study. Of note, this course applies precalculus and calculus; this is different from “applied math,” which economists typically use to refer to probability and statistics. This course begins with a survey of basic optimization tools and then applies them to solve problems over several periods in time. These optimization tools descri…
This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed for further study of econometrics and provide basic preparation for 14.32. Topics include elements of probability theory, sampling theory, statistical estimation, and hypothesis testing.
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.
Marketing research may be divided into methods that emphasize understanding "the customer" and methods that emphasize understanding "the market." This course (15.822) deals with the market. The companion course (15.821) deals with the customer.
The course will teach you how to write, conduct and analyze a marketing research survey. The emphasis will be on discovering market structure and segmentation, but you can pursue other project applications.
A major objective of the course is to give you some "hands-on" exposure to analysis techniques that are widely used in consulting and marketing research factor analysis, perceptual mapping, conjoint, and cluster analysis). These techniques used to be considered advanced but now involve just a few keystrokes on most stat software packages.
The course assumes familiarity with basic probability, statistics, and multiple linear regression.
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