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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/business-data
课程评论：没有评论
课程名称：探索与生产企业决策数据 概述：本课程提供了一种分析框架，帮助您以结构化的方式评估关键问题，并为您提供更好地管理企业流程中固有不确定性的工具。您将学习如何总结数据，掌握频率、正态分布、统计研究、抽样和置信区间等概念。 尽管课程将介绍一些科学原理，但重点在于应用方法论。课程将借助Excel和来自不同学科的数据集，展示统计在多种情境中的应用。课程不仅将解释这些概念，还将帮助您理解和解读所获得的结果。 您将能够： • 以图形、表格和数值的形式总结大量数据集 • 理解适当抽样的重要性以及为何可以依赖样本信息 • 了解为何正态分布可广泛应用于多种情境 • 利用样本信息对总体作出推断，具有一定的准确性信心水平 • 使用Excel进行统计分析 本课程属于Gies商学院的在线课程系列，包括iMBA和iMSM项目。有关这些项目的入学信息，您可访问https://degrees.giesbusiness.illinois.edu/idegrees/了解更多。 课程大纲： 1. 课程介绍：熟悉课程内容、同学和学习环境，获取所需的技术技能。 2. 数据描述和总结：学习统计工具，以更好地理解收集到的信息，从而做出更好的决策。 3. 描述性统计与概率分布：学习如何利用图像简化数据的理解。 4. 抽样与中心极限定理：探讨如何获取数据，并理解如何产生有效的样本数据和中心极限定理的概念。 5. 推断：在拥有样本数据和分析结果后，学习如何评估推断的准确性以及应考虑的其他因素。
Name:Course Orientation
Description:You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
Name:Module 1: Introduction and Summarizing Data
Description:Data is all around you, but what is the data telling you? The first step in making better decisions and taking action is to get a good understanding of information you have gathered. In this module we will learn about some of the tools in statistics that help us achieve this.
Name:Module 2: Descriptive Statistics and Probability Distributions
Description:We all have heard the phrase that a "picture is worth a thousand words," but you certainly don’t want one of those to be "what exactly am I looking at?" So, now that you know to use "pictures" to summarize your data, let’s make those pictures easier to understand.
Name:Module 3: Sampling and Central Limit Theorem
Description:You are charged with analyzing a market segment for your company. You and your team have figured out what variables you need to understand; you also have an idea what factors might be influencing these variables of interest. Now you are ready to do your analysis. But, wait! Where is the data? How do you begin to get the data? In this module we will review the means by which you can begin to produce data – the concepts of sampling and Central Limit Theorem – and will help you understand how to produce "good" sample data and why sample data will work.
Name:Module 4: Inference
Description:You have sample data and have done the analysis – you think you can say something about the population based on your sample study. But, do you have a sense of what are the chances of you being right or wrong? How can you be surer? What else should you have considered? In this module, you will learn how to find the answers to these questions.
This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. Specifically, you will learn how to summarize data and learn concepts of frequency, normal distribution, statistical studies, sampling, and confidence intervals. While you will be introduced to some of the science of what is being taught, the focus will be on applying the methodologies. This will be accomplished through the use of Excel and data sets from different disciplines, allowing you to see the use of statistics in a range of settings. The course will focus not only on explaining these concepts, but also understanding and interpreting the results obtained. You will be able to: • Summarize large data sets in graphical, tabular, and numerical forms • Understand the significance of proper sampling and why one can rely on sample information • Understand why normal distribution can be used in a wide range of settings • Use sample information to make inferences about the population with a certain level of confidence about the accuracy of the estimations • Use Excel for statistical analysis This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.
