Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

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Rice University

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The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course. To successfully complete course assignments, students must have access to Microsoft Excel. ________________________________________ WEEK 1 Module 1: Basic Data Descriptors In this module you will get to understand, calculate and interpret various descriptive or summary measures of data. These descriptive measures summarize and present data using a few numbers. Appropriate Excel functions to do these calculations are introduced and demonstrated. Topics covered include: • Categories of descriptive data • Measures of central tendency, the mean, median, mode, and their interpretations and calculations • Measures of spread-in-data, the range, interquartile-range, standard deviation and variance • Box plots • Interpreting the standard deviation measure using the rule-of-thumb and Chebyshev’s theorem ________________________________________ WEEK 2 Module 2: Descriptive Measures of Association, Probability, and Statistical Distributions This module presents the covariance and correlation measures and their respective Excel functions. You get to understand the notion of causation versus correlation. The module then introduces the notion of probability and random variables and starts introducing statistical distributions. Topics covered include: • Measures of association, the covariance and correlation measures; causation versus correlation • Probability and random variables; discrete versus continuous data • Introduction to statistical distributions ________________________________________ WEEK 3 Module 3: The Normal Distribution This module introduces the Normal distribution and the Excel function to calculate probabilities and various outcomes from the distribution. Topics covered include: • Probability density function and area under the curve as a measure of probability • The Normal distribution (bell curve), NORM.DIST, NORM.INV functions in Excel ________________________________________ WEEK 4 Module 4: Working with Distributions, Normal, Binomial, Poisson In this module, you'll see various applications of the Normal distribution. You will also get introduced to the Binomial and Poisson distributions. The Central Limit Theorem is introduced and explained in the context of understanding sample data versus population data and the link between the two. Topics covered include: • Various applications of the Normal distribution • The Binomial and Poisson distributions • Sample versus population data; the Central Limit Theorem

基本数据描述符,统计分布以及在业务决策中的应用:了解和应用业务统计的能力在行业中变得越来越重要。对业务统计数据有充分的了解是对数据进行正确且相关的解释的要求。缺乏知识可能导致错误的决策,这可能会对公司产生负面影响。本课程旨在向您介绍商业统计。我们从描述性统计的概念开始,即使用一些数字对数据进行汇总。介绍并讨论了不同类别的描述性度量以及Excel函数以对其进行计算。概率或不确定性的概念与样本和总体数据的概念一起使用相关的业务示例进行了介绍。这将导致我们获得各种统计分布以及它们的Excel函数,然后将其用于建模或近似业务流程。您将使用易于理解的基于Excel的示例来应用这些数据和各种统计分布的描述性度量,这些示例将在整个课程中进行演示。 要成功完成课程分配,学生必须有权使用Microsoft Excel。 ________________________________________ 第1周 模块1:基本数据描述符 在本模块中,您将了解,计算和解释各种描述性或汇总性数据度量。这些描述性措施使用一些数字汇总并显示了数据。介绍并演示了用于执行这些计算的适当Excel函数。 涵盖的主题包括: •描述性数据的类别 •集中趋势的度量,均值,中位数,众数及其解释和计算 •数据散布,范围,四分位范围,标准差和方差的度量 •箱形图 •使用经验法则和切比雪夫定理解释标准差测度 ________________________________________ 第2周 模块2:关联性,概率和统计分布的描述性度量 该模块介绍了协方差和相关性度量及其各自的Excel函数。您将了解因果关系与相关性的概念。然后,模块介绍概率和随机变量的概念,并开始介绍统计分布。 涵盖的主题包括: •关联度量,协方差和相关度量;因果关系 •概率和随机变量;离散数据与连续数据 •统计分布简介 ________________________________________ 第3周 模块3:正态分布 该模块引入了正态分布和Excel函数,以计算概率和分布的各种结果。 涵盖的主题包括: •概率密度函数和曲线下面积作为概率的量度 •Excel中的正态分布(钟形曲线),NORM.DIST,NORM.INV函数 ________________________________________ 第4周 单元4:使用分布,正态,二项式,泊松 在本模块中,您将看到正态分布的各种应用。您还将了解二项式和泊松分布。在理解样本数据与总体数据以及两者之间的联系的背景下,介绍并解释了中心极限定理。 涵盖的主题包括: •正态分布的各种应用 •二项式和泊松分布 •样本与人口数据;中心极限定理

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