商务统计学Ch01
商务统计章节知识点总结
商务统计章节知识点总结第一章：统计学基础概念1.1 统计学的概念和作用统计学是一门研究数据收集、整理、分析和解释的学科，通过统计学的方法可以对数据进行分析和推断，以便做出科学决策。
在商务领域，统计学可以帮助企业分析市场、预测销售和制定营销策略。
1.2 统计学的基本原理统计学的基本原理包括总体和样本、变量、数据类型、测度尺度等内容。
理解这些基本原理对于进行商务统计分析非常重要。
1.3 统计学的应用范围统计学在商务领域有广泛的应用，包括市场调研、销售预测、风险评估、财务分析等方面。
第二章：数据类型和数据收集2.1 数据的类型数据可以分为定量数据和定性数据，定量数据可以进一步分为禺式数据和顺序数据，定性数据可以进一步分为名义数据和区间数据。
理解不同类型的数据对于选择合适的统计分析方法非常重要。
2.2 数据的收集方法数据的收集方法包括问卷调查、访谈、实地观察、记录和外部数据收集等。
在商务统计分析中，选择合适的数据收集方法对于数据的质量至关重要。
第三章：统计描述与概率分布3.1 描述统计描述统计是对数据进行整理、描述、总结和展示的过程，包括中心位置测度、离散程度测度、分布形态测度等内容。
在商务统计分析中，描述统计可以帮助我们了解数据的特征和规律。
3.2 概率分布概率分布描述了随机变量的取值及其对应的概率，包括离散型概率分布和连续型概率分布。
在商务统计分析中，概率分布可以帮助我们理解不同变量之间的关系和规律。
第四章：抽样与估计4.1 抽样方法抽样是指从总体中选取样本的过程，常用的抽样方法包括简单随机抽样、分层抽样、整群抽样和多阶段抽样等。
在商务统计分析中，选择合适的抽样方法对于大规模数据的分析非常重要。
4.2 估计估计是根据样本数据对总体参数进行估计的过程，包括点估计和区间估计两种方法。
在商务统计分析中，通过估计可以得到总体参数的近似值，用于制定决策和预测。
第五章：假设检验与单因素方差分析5.1 假设检验假设检验是用来检验统计结论的正确性的方法，包括参数假设检验和非参数假设检验两种方法。
商务统计学
二、分布中心测度指标
用来测度随机变量次数分布中心的 指标可以有多种，其中在统计分析推断 中常用的主要有算术平均数、中位数和 众数等几种。
（一）算术平均数
1、定义——算术平均数又称算术均值，是 随机变量的所有观测值总和与观测值个 数的比值。
（一）两点分布
假设总体中有两类共N个个体，其中取 值为“是”的有N1个，取值为“非”的有N0 个，则有：
P x 1 N 1 p
N
Px 0 N 0 q
N
（二）二项分布
假设在0-1分布总体中，取“是”值的 个体比例为p，取“非”值的比例为q，现 从中有放回地随机抽取n个个体，记X为取 “是”值的个体数目，则其中恰有n1个个 体取“是”值、且有n0=n-n1个个体取“非” 值的概率为：
第一章 绪论
➢一、统计学的性质 ➢二、统计学的作用 ➢三、统计学的基本概念 ➢四、统计指标体系的设计
一、统计学的性质
• （一）统计活动的内容与阶段 • 对各种数据资料的搜集、整理、分析和推断的
活动过程称为统计活动，一项完整的统计活动过程 可分为统计资料的搜集整理和统计资料的分析推断 两大阶段。 • （二）统计学的定义与分科 • 统计学就是关于数据资料的搜集、整理、分析 和推断的科学。关于统计资料的搜集整理和分析推 断的理论与方法构成了统计学的全部内容。 • （1）理论统计学与应用统计学 • （2）描述统计学与推断统计学
P x n 1 C n n 1p n 1 q n 0
（三）超几何分布
假设0-1总体中共有N个个体，其中取
“是”值的个体有N1个，取“非”值的 个体有N0个。现从不放回地随机抽取n个 个体，记x为取“是”值的个体数目，则
第一章 商务统计学样本
e.g., Tables and graphs 分析图表
Characterize data（刻画数据的特征）
e.g., Sample mean =
X
n
i
（样本均值）
Chap 1-7
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
The types of data used in business 商业活动中使用数据 的类型 The basics of Microsoft Excel Excel基础 The basics of Minitab 统计软件Minitab基础
Cha Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
Present and describe business data and information properly 正确的展示和描述商业数据的和信息（描述性统计） Draw conclusions about large groups of individuals or items, using information collected from subsets of the individuals or items. 利用收集到的个体或者商品的子集数据来推断有关更广范围内个体 或者商品的结论（推断统计） Make reliable forecasts about a business activity 为商业活动提供可靠的预测（推断统计） Improve business processes 改善商业活动的过程
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
商务统计学第一章
xx年xx月xx日
contents
目录
• 引言 • 商务统计学基本概念 • 数据类型与数据收集 • 数据的整理与可视化 • 概率论基础
contents
目录
• 统计推断基础 • 相关分析与回归分析 • 时间序列分析与预测 • 统计决策理论
01
引言
课程简介
商务统计学是统计学在商业和经济领域的应用，旨在培养学 生在商业和经济领域运用统计学方法解决实际问题的能力。
统计学的发展经历了描述性统计学、推断性 统计学和现代统计学三个阶段。
描述性统计学主要是对数据进行描述性统计 指标的计算和数据的可视化，推断性统计学 主要是通过样本信息对总体进行推断和分析 ，现代统计学则涉及到数据挖掘、机器学习
、时间序列分析等多个方面。
02
商务统计学基本概念
统计学的定义
统计学是一门收集、整理、分析和 解释数据的科学。
基于一组变量预测另一个变量的值。
选择变量、收集数据、建立模型、检 验模型、应用模型。
03
回归分析的基本假设
线性关系、误差项独立同分布、误差 项无序列相关性、解释变量与误差项 无多重共线性。
线性回归模型
线性回归模型的定义
一种用于预测的模型，将解释变 量与响应变量之间的关系建模为 线性关系。
线性回归模型的参数 估计
数据收集的方法
调查问卷
通过邮寄、网络或现场发放问卷， 收集相关数据
观察法
记录现场观察到的数据，如销售额 、客流量等
实验法
通过实验来测试不同因素对变量的 影响，如A/B测试
现有统计数据
从政府、企业或第三方机构获取相 关统计数据
数据收集的步骤
01
商务统计课程介绍及学习要求
课程内容
时间序列分析部分 时间序列数据的特点是自相关性，其 变化的动因分析是该部分的重点内容。 多变量数据分析 自然界、社会、经济系统中的变量之 间都不是独立的，探讨彼此之间的结 构关系是非常重要的。
教学要求
一、成绩评定 1、课堂参与：以小组（随机分组）为 单位计分 2、学习态度：满分100分，旷课一次扣 10分，请假一次扣5分； 3、项目作业：以小组为单位自选课题 4、期末考试：期末闭卷考试
为了便于借鉴，各小组查找一篇有关 “商务统计”应用的论文（可上网搜索） 并要求看懂，并搞清如下问题：
1. 论文的选题意义？ 2. 数据是如何获取的？ 3. 采用什么分析方法？ 4. 分析的结果如何与实际要解决的问 题联系起来的？ 5. 得出什么结论？
教学要求
二、项目作业及要求 自选一个课题，建立一个包含两个自变 量（或以上）的回归模型，写出一份书 面分析报告（WORD文档）并作成口头 报告文档（PPT文档）。
教学要求
二、项目作业书面分析报告具体格式及要求如 下： 1、引言—选题的背景及意义； 2、数据来源及分析方法；
（1）说明数据的出处并初步分析所取数据是否满 足回归模型以及理论的要求。 （2）说明所用的统计方法（必须包括多元线性回 归分析）；
5、参考文献 列出本文在形成过程中的所有重要参考文献 附录:
1、收获与体会。 2、原始数据 3、如自己收集数据的需附问卷
教学要求
二、项目作业PPT报告具体要求如下： 1、简明扼要，将研究的主要结果给以展示； 2、生动活泼具有可观性
教学要求
三、项目作业评分（100分） 项目作业从7个方面进行评分： 1、选题意义（20%） 2、数据分析（20%） 3、建模合理性（15%） 4、模型评价（15%） 5、写作规范性（WORD文档） （10%） 6、报告水平（10%） 7、PPT制作（10%）
商务统计学知识要点
商务统计学知识要点
一、统计资料。
指通过统计工作取得的、用来反映社会经济现象的数据资料的总称。
统计工作所取得的各项数字资料及有关文字资料，一般反映在统计表、统计图、统计手册、统计年鉴、统计资料汇编和统计分析报告中。
也称统计信息，是反映一定社会经济现象总体或自然现象总体的特征或规律的数字资料、文字资料、图表资料及其他相关资料的总称。
包括刚刚调查取得的原始资料和经过一定程度整理、加工的次级资料，其形式有：统计表、统计图、统计年鉴、统计公报、统计报告和其他有关统计信息的载体。
二、统计科学。
也称统计学，是统计工作经验的总结和理论概括，是系统化的知识体系。
指研究如何搜集、整理和分析统计资料的理论与方法。
统计学是应用数学的一个分支，主要通过利用概率论建立数学模型，收集所观察系统的数据，进行量化的分析、总结，并进而进行推断和预测，为相关决策提供依据和参考。
它被广泛的应用在各门学科之上，从物理和社会科学到人文科学，甚至被用来工商业及政客用来研究参考。
商务统计实验报告总结
一、实验背景随着我国经济的快速发展，商务活动日益频繁，数据的收集、处理和分析在商务决策中扮演着越来越重要的角色。
为了提高学生的商务统计素养，我们开展了商务统计实验课程。
通过本实验，使学生掌握商务统计的基本原理、方法和应用，提高学生运用统计方法分析和解决实际问题的能力。
二、实验目的1. 理解商务统计的基本概念和原理；2. 掌握商务统计数据的收集、整理和分析方法；3. 培养学生运用统计方法分析和解决实际问题的能力；4. 提高学生商务统计素养，为今后从事相关工作奠定基础。
三、实验内容本次实验主要分为以下几个部分：1. 商务统计数据的基本概念与原理介绍了商务统计的基本概念、数据类型、数据收集方法等，并分析了商务统计数据的特征和规律。
2. 商务统计数据的收集与整理讲解了商务统计数据的收集方法，包括直接调查、间接调查、问卷调查等；同时，介绍了数据整理的基本步骤和常用方法。
3. 商务统计数据的描述性分析运用图表、数值等方法对商务统计数据进行了描述性分析，包括集中趋势、离散趋势和分布形态等。
4. 商务统计数据的推断性分析介绍了商务统计推断的基本原理和方法，包括参数估计和假设检验等。
通过实例分析，使学生掌握了如何运用统计方法对商务数据进行推断。
5. 商务统计软件的应用利用统计软件（如SPSS、Excel等）进行商务统计数据的处理和分析，提高了学生的实际操作能力。
四、实验过程1. 学生分组：将学生分成若干小组，每组负责一个实验项目。
2. 实验指导：教师对实验内容进行讲解，并对实验过程中可能遇到的问题进行解答。
3. 数据收集：各组根据实验要求，收集相关的商务统计数据。
4. 数据处理：各组运用统计软件对收集到的数据进行整理和分析。
5. 实验报告：各组撰写实验报告，总结实验过程中的收获和体会。
五、实验结果与分析1. 学生通过本次实验，对商务统计数据的基本概念、原理和方法有了更深入的理解。
2. 学生掌握了商务统计数据的收集、整理和分析方法，提高了运用统计方法分析和解决实际问题的能力。
统计学(中英文)_ch01
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Chap 1-12
∑X
n
i
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Chap 1-8
Inferential Statistics 推断统计
Estimation 估计 e.g., Estimate the population mean weight using the sample mean weight 例如：利用采样的平均重量估计人口的平均体 重 Hypothesis testing 假设检验 e.g., Test the claim that the population mean weight is 120 pounds 例如：根据测试的要求，人口平均体重是120 磅
英文翻译乃自己所做， 英文翻译乃自己所做，有错误 之处请自行查证。 之处请自行查证。
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Chap 1-1
Business Statistics, A First Course
Defined descriptive vs. inferential statistics 描述性统计和推理统计 Reviewed data types 回顾数据类型
♦ ♦ ♦ ♦
Categorical vs. Numerical data 绝对的和数值的数据 Discrete vs. Continuous data 离散的和连续的数据
商务统计学第一章
总体与样本
例如，研究全国服务业企业的利润情况时，全国所有的服务业企业 形成了一个总体。成千上万不同的服务业企业可以结合在一起构成总体， 这是因为每个服务业企业的经济职能是相同的，都是从事生产和销售服 务产品的基本单位，在经营过程中都需要投入一定的成本以获取相应的 收益。同质性是确定总体的基本标准，它是根据研究目的而确定的。研 究目的不同，则所确定的总体也不同，其同质性的意义也随之变化。
工作等有什么特别意义呢？
数据
统计学研究的基础是数据。数据，就其词义而言， 指进行各种统计、计算、科学研究和技术设计等所依据 的数值。
英语里data作为datum一词的复数形式，具有如下 涵义：①论据，作为论据的事实；②材料，资料； ③历史上的、计算或实验得到的数据。
数据
数据本身没有意义，数据只有对实体行为产生影响 时才成为信息，其反映的是一定社会现象或自然现象在 特定的时间、空间条件下表现出的特征，故商务活动领 域分析研究的数据需要具备时间与空间要素，并非数学 学科中纯粹的、抽象的数字。
只能归于某一类别的非数值型数据 对事物进行分类的结果，数据表现为类别，用文字、代码和其
他符号来表述 例如，人口按性别分为男、女两类
定序标志与数据
1. 定序标志：说明事物有序类别的名称
受教育程度、产业、等级等
2. 定序数据：
只能归于某一有序类别的非数字型数据 对事物类别顺序的测度，数据表现为类别，用文字来表述 例如，产品分为一等品、二等品、三等品、次品等
1. 标志是指统计总体各单位所具有的共同 特征的名称。
2. 数据是标志特征在各单位的具体表现
Variale and Data
标志与数据
定类标志 定序标志 定距标志 定比标志 定类数据 定序数据 定距数据 定比数据
戴维商务统计学第7版英文版教学指南CH01_Levine7e_ISM
Solutions to End-of-Section and Chapter Review Problems 31CHAPTER 11.1 The type of beverage sold yields categorical or “qualitative” responses.The type of beverage sold yields distinct categories in which no ordering is implied.1.2 Three sizes of U.S. businesses are classified into distinct categories—small, medium, and large—in which order is implied.1.3 The time it takes to download a video from the Internet is a continuous numerical or“quantitative” variable because time can have any value from 0 to any reasonable unit of time.1.4 (a) The number of cellphones is a numerical variable that is discrete because the outcome isa count.(b) Monthly data usage is a numerical variable that is continuous because any value within arange of values can occur.(c) Number of text messages exchanged per month is a numerical variable that is discretebecause the outcome is a count.(d) Voice usage per month is a numerical variable that is continuous because any valuewithin a range of values can occur.(e) Whether a cellphone is used for email is a categorical variable because the answer can beonly yes or no.1.5 (a) numerical, continuous(b) numerical, discrete(c) categorical(d) categorical1.6 (a) Categorical(b) Numerical, continuous(c) Categorical(d) Numerical, discrete(e) Categorical1.7 (a) numerical, continuous *(b) categorical(c) categorical(d) numerical, discrete*Some researchers consider money as a discrete numerical variable because it can be “counted.”1.8 (a) numerical, continuous *(b) numerical, discrete(c) numerical, continuous *(d) categorical*Some researchers consider money as a discrete numerical variable because it can be “counted.”32 Chapter 1: Defining and Collecting Data1.9 (a) Income may be considered discrete if we “count” our money. It may be consideredcontinuous if we “measure” our money; we are only limited by the way a country'smonetary system treats its currency.(b) The first format is preferred because the responses represent data measured on a higherscale.1.10 The underlying variable, ability of the students, may be continuous, but the measuring device, thetest, does not have enough precision to distinguish between the two students.1.11 (a) The population is “all working women from the metropolitan area.” A systematic or randomsample could be taken of women from the metropolitan area. The director might wish tocollect both numerical and categorical data.(b) Three categorical questions might be occupation, marital status, type of clothing.Numerical questions might be age, average monthly hours shopping for clothing, income.1.12 The answer depends on the chosen data set.1.13 The answer depends on the specific story.1.14 The answer depends on the specific story.1.15 The transportation engineers and planners should use primary data collected through anobservational study of the driving characteristics of drivers over the course of a month.1.16 The information presented there is based mainly on a mixture of data distributed by anorganization and data collected by ongoing business activities.1.17 (a) 001 (b) 040 (c) 9021.18 Sample without replacement: Read from left to right in 3-digit sequences and continue unfinishedsequences from end of row to beginning of next row.Row 05: 338 505 855 551 438 855 077 186 579 488 767 833 170Rows 05-06: 897Row 06: 340 033 648 847 204 334 639 193 639 411 095 924Rows 06-07: 707Row 07: 054 329 776 100 871 007 255 980 646 886 823 920 461Row 08: 893 829 380 900 796 959 453 410 181 277 660 908 887Rows 08-09: 237Row 09: 818 721 426 714 050 785 223 801 670 353 362 449Rows 09-10: 406Note: All sequences above 902 and duplicates are discarded.1.19 (a) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86 92 71Note: All sequences above 93 and all repeating sequences are discarded.(b) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86Note: All sequences above 93 are discarded. Elements 65 and 83 are repeated.Solutions to End-of-Section and Chapter Review Problems 33 1.20 A simple random sample would be less practical for personal interviews because of travel costs(unless interviewees are paid to attend a central interviewing location).1.21 This is a probability sample because the selection is based on chance. It is not a simple randomsample because A is more likely to be selected than B or C.1.22 Here all members of the population are equally likely to be selected and the sample selectionmechanism is based on chance. But not every sample of size 2 has the same chance ofbeing selected. For example the sample “B and C” is impossible.1.23 (a) Since a complete roster of full-time students exists, a simple random sample of 200students could be taken. If student satisfaction with the quality of campus life randomlyfluctuates across the student body, a systematic 1-in-20 sample could also be taken fromthe population frame. If student satisfaction with the quality of life may differ by genderand by experience/class level, a stratified sample using eight strata, female freshmenthrough female seniors and male freshmen through male seniors, could be selected. Ifstudent satisfaction with the quality of life is thought to fluctuate as much within clustersas between them, a cluster sample could be taken.(b) A simple random sample is one of the simplest to select. The population frame is theregistrar’s file of 4,000 student names.(c) A systematic sample is easier to select by hand from the registrar’s records than asimple random sample, since an initial person at random is selected and then every 20thperson thereafter would be sampled. The systematic sample would have the additionalbenefit that the alphabetic distribution of sampled students’ names would be morecomparable to the alphabetic distribution of student names in the campus population.(d) If rosters by gender and class designations are readily available, a stratified sampleshould be taken. Since student satisfaction with the quality of life may indeed differ bygender and class level, the use of a stratified sampling design will not only ensure allstrata are represented in the sample, it will also generate a more representative sampleand produce estimates of the population parameter that have greater precision.(e) If all 4,000 full-time students reside in one of 10 on-campus residence halls which fullyintegrate students by gender and by class, a cluster sample should be taken. A clustercould be defined as an entire residence hall, and the students of a single randomlyselected residence hall could be sampled. Since each dormitory has 400 students, asystematic sample of 200 students can then be selected from the chosen cluster of 400students. Alternately, a cluster could be defined as a floor of one of the 10 dormitories.Suppose there are four floors in each dormitory with 100 students on each floor. Twofloors could be randomly sampled to produce the required 200 student sample. Selectionof an entire dormitory may make distribution and collection of the survey easier toaccomplish. In contrast, if there is some variable other than gender or class that differsacross dormitories, sampling by floor may produce a more representative sample.34 Chapter 1: Defining and Collecting Data1.24 (a) Row 16: 2323 6737 5131 8888 1718 0654 6832 4647 6510 4877Row 17: 4579 4269 2615 1308 2455 7830 5550 5852 5514 7182Row 18: 0989 3205 0514 2256 8514 4642 7567 8896 2977 8822Row 19: 5438 2745 9891 4991 4523 6847 9276 8646 1628 3554Row 20: 9475 0899 2337 0892 0048 8033 6945 9826 9403 6858Row 21: 7029 7341 3553 1403 3340 4205 0823 4144 1048 2949Row 22: 8515 7479 5432 9792 6575 5760 0408 8112 2507 3742Row 23: 1110 0023 4012 8607 4697 9664 4894 3928 7072 5815Row 24: 3687 1507 7530 5925 7143 1738 1688 5625 8533 5041Row 25: 2391 3483 5763 3081 6090 5169 0546Note: All sequences above 5000 are discarded. There were no repeating sequences.(b) 089 189 289 389 489 589 689 789 889 9891089 1189 1289 1389 1489 1589 1689 1789 1889 19892089 2189 2289 2389 2489 2589 2689 2789 2889 29893089 3189 3289 3389 3489 3589 3689 3789 3889 39894089 4189 4289 4389 4489 4589 4689 4789 4889 4989(c) With the single exception of invoice #0989, the invoices selected in the simplerandom sample are not the same as those selected in the systematic sample. It would behighly unlikely that a random process would select the same units as a systematicprocess.1.25 (a) A stratified sample should be taken so that each of the three strata will be proportionatelyrepresented.(b) The number of observations in each of the three strata out of the total of 1,000 shouldreflect the proportion of the three categories in the customer database. For example,3,500/10,000 = 35% so 35% of 1,000 = 350 customers should be selected from theprospective buyers; similarly 4,500/10,000 = 45% so 450 customers should be selectedfrom the first time buyers, and 2,000/10,000 = 20% so 200 customers from the repeatbuyers.(c) It is not simple random sampling because, unlike the simple random sampling, it ensuresproportionate representation across the entire population.1.26 Before accepting the results of a survey of college students, you might want to know, forexample:Who funded the survey? Why was it conducted? What was the population from which the sample was selected? What sampling design was used? What mode of response was used: a personalinterview, a telephone interview, or a mail survey? Were interviewers trained? Were surveyquestions field-tested? What questions were asked? Were they clear, accurate, unbiased, valid?What operational definition of “vast majority” was used? What was the response rate? What was the sample size?1.27 (a) Possible coverage error: Only employees in a specific division of the company weresampled.(b) Possible nonresponse error: No attempt is made to contact nonrespondents to urge themto complete the evaluation of job satisfaction.(c) Possible sampling error: The sample statistics obtained from the sample will not be equalto the parameters of interest in the population.(d) Possible measurement error: Ambiguous wording in questions asked on thequestionnaire.Solutions to End-of-Section and Chapter Review Problems 35 1.28 The results are based on an online survey. If the frame is supposed to be small business owners,how is the population defined? This is a self-selecting sample of people who responded online, so there is an undefined nonresponse error. Sampling error cannot be determined since this is not a random sample.1.29 Before accepting the results of the survey, you might want to know, for example:Who funded the study? Why was it conducted? What was the population from which the sample was selected? What was the frame being used? What sampling design was used?What mode of response was used: a personal interview, a telephone interview, or a mail survey?Were interviewers trained? Were survey questions field-tested? What other questions wereasked? Were they clear, accurate, unbiased, and valid? What was the response rate? What was the margin of error? What was the sample size?1.30 Before accepting the results of the survey, you might want to know, for example: Who funded thestudy? Why was it conducted? What was the population from which the sample was selected?What sampling design was used? What mode of response was used: a personal interview, atelephone interview, or a mail survey? Were interviewers trained? Were survey questions field-tested? What other questions were asked? Were the questions clear, accurate, unbiased, andvalid? What was the response rate? What was the margin of error? What was the sample size?What frame was used?1.31 A population contains all the items of interest whereas a sample contains only a portion of theitems in the population.1.32 A statistic is a summary measure describing a sample whereas a parameter is a summary measuredescribing an entire population.1.33 Categorical random variables yield categorical responses such as yes or no answers. Numericalrandom variables yield numerical responses such as your height in inches.1.34 Discrete random variables produce numerical responses that arise from a counting process.Continuous random variables produce numerical responses that arise from a measuring process.1.35 Items or individuals in a probability sampling are selected based on known probabilities whileitems or individuals in a nonprobability samplings are selected without knowing theirprobabilities of selection.1.36 Microsoft Excel could be used to perform various statistical computations that were possible onlywith a slide-rule or hand-held calculator in the old days.1.37 (a) The population of interest was 18-54 year olds who currently own a smartphone and/ortablet, and who use and do not use these devices to shop.(b) The sample was the 1,003 18-54 year olds who currently own a smartphone and/or tablet,who use and do not use these devices to shop, and who responded to the study.(c) A parameter of interest is the proportion of all tablet users in the population who use theirdevice to purchase product and services.(d) A statistic used to estimate the parameter of interest in (c) is the proportion of tablet usersin the sample who use their device to purchase product and services.36 Chapter 1: Defining and Collecting Data1.38 The answers to this question depend on which article and its corresponding data set is beingselected.1.39 (a) The population of interest was supply chain executives in a wide range of industriesrepresenting a mix of company sizes from across three global regions: Asia, Europe, andthe Americas.(b) The sample was the 503 supply chain executives in a wide range of industriesrepresenting a mix of company sizes from across three global regions: Asia, Europe, andthe Americas surveyed by PwC from May to July 2012.(c) A parameter of interest is the proportion of supply chain executives in the populationwho acknowledge that supply chain is seen as a strategic asset in their company.(d) A statistic used to estimate the parameter of interest in (c) is the proportion of supplychain executives in the sample who acknowledge that supply chain is seen as a strategicasset in their company.1.40 The answers to this question depend on which data set is being selected.1.41 (a) Categorical variable: Which of the following best describes this firm’s primary business?(b) Numerical variable: On average, what percent of total monthly revenues are e-commercerevenues?1.42 (a) The population of interest was the collection of all the 10,000 benefitted employees at theUniversity of Utah when the study was conducted.(b) The sample consisted of the 3,095 benefitted employees participated in the study.(c) gender: categorical; age: numerical; education level: numerical; marital status:categorical; household income: numerical; employment category: categorical1.43 (a) (i)categorical (iii) numerical, discrete(ii)categorical (iv) categorical(b) The answers will vary.(c) The answers will vary.。
应用商务统计学讲义第一章中英文对照版
• “Big data” or very large data sets are arising because of the automatic collection of high volumes of data at very fast rates. •“大数据”或非 常大的数据集的出现，是因为以非常快的速率自动收集大量数据 6 。
– Element: an entity or object on which data are collected. Also called case, subject, individual, item-
– 元素：收集数据的实体或对象。也称案件、主体、个人、项目
– Observation: measurement of a variable on a single element
使用DCOVA框架帮助你申请统计：
• Summarize & visualize business data • 总结和可视化业务数据 • Reach conclusions from those data • 从这些数据中得出结论 • Make reliable forecasts about business activities • 对业务活动作出可靠的预测 • Improve business processes • 改进业务流程
No order
ordered/ ranked
No true zero
Absolute zero
Difference is meaningful Difference is meaninபைடு நூலகம்ful
英文商务统计学ppt课件第一章_Ch01
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
Chap 1-3
What is statistics?
A branch of mathematics taking and transforming numbers into useful information for decision makers
Methods for processing & analyzing numbers Methods for helping reduce the uncertainty inherent in decision making
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
Chap 1-1
Learning Objectives
In this chapter you learn:
How Statistics is used in business The sources of data used in business The types of data used in business
Chap 1-4
Why Study Statistics?
Decision Makers Use Statistics To:
Present and describe business data and information properly Draw conclusions about large groups of individuals or items, using information collected from subsets of the individuals or items. Make reliable forecasts about a business activity Improve business processes
商务统计学课件第1章(ISEC)
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Hale Waihona Puke Chap 1-4附注在商业世界中，统计学有4种重要的应用。
· 总结商业数据 · 根据数据得出结论 · 作出商业行动的可靠预测 · 改进运营过程
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Chap 1-10
为什么要收集数据？
市场调研者需要了解一个新的旅游产品的效果； 消费者的消费行为方面的信息数据，如：消费者购买产 品的花费、选择的产品渠道、偏好产品的类型、产品使 用周期、购买产品的目的、消费者家庭背景、工作和生 活环境、个人消费观和价值观等。如果企业收集到了这 些数据，建立消费者大数据库，便可通过统计和分析来 掌握消费者的消费行为、兴趣偏好和产品的市场口碑现 状，再根据这些总结出来的行为、兴趣爱好和产品口碑 现状制定有针对性的营销方案和营销战略，投消费者所 好，那么其带来的营销效应是可想而知的。
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc.
Chap 1-16
Types of Data（数据类型）
Data
（属性） Categorical
Examples:
Numerical （数值）
gender belief (Defined categories) 定义属性类别
Probability Theory & Mathematical Statistics 概率论与数理统计
商务统计学_教学的实践(3篇)
第1篇一、引言随着我国经济的快速发展，统计学在商务领域的应用越来越广泛。
商务统计学作为一门重要的学科，旨在培养学生的统计学思维和分析能力，使其能够运用统计学的方法解决实际问题。
本文将从以下几个方面探讨商务统计学教学的实践。
二、教学目标1. 理解商务统计学的基本概念、原理和方法。
2. 掌握商务统计数据的收集、整理和分析方法。
3. 能够运用统计学方法对商务问题进行定量分析和预测。
4. 培养学生的统计学思维和分析能力，提高解决实际问题的能力。
三、教学内容1. 商务统计学基本概念：包括数据、变量、总体、样本、概率、分布等。
2. 商务统计数据的收集：介绍数据来源、数据类型、数据收集方法等。
3. 商务统计数据的整理：介绍数据的整理方法，如分组、排序、计算等。
4. 商务统计数据的分析：介绍描述性统计、推断性统计、时间序列分析等。
5. 商务统计应用：结合实际案例，分析商务问题，运用统计学方法进行定量分析和预测。
四、教学实践1. 案例教学：选取具有代表性的商务案例，让学生分析案例中的统计学问题，引导学生运用所学知识解决实际问题。
2. 实践操作：组织学生进行商务统计数据收集、整理和分析的实践活动，让学生亲身体验统计学在实际工作中的应用。
3. 讨论与交流：组织学生进行课堂讨论，分享各自的学习心得和经验，提高学生的合作意识和沟通能力。
4. 考核评价：采用多种考核方式，如课堂表现、作业、实践报告、期末考试等，全面评价学生的学习成果。
五、教学手段1. 课堂教学：运用多媒体技术，展示丰富的教学资源，提高学生的学习兴趣。
2. 网络教学：利用网络平台，为学生提供在线学习资源，方便学生随时随地进行学习。
3. 实践基地：与企业合作，建立商务统计学实践教学基地，为学生提供实际操作机会。
4. 专家讲座：邀请统计学专家进行讲座，为学生提供专业指导。
六、教学效果1. 学生对商务统计学的基本概念、原理和方法有了深入的理解。
2. 学生的商务统计数据收集、整理和分析能力得到提高。
商务统计-C11
Chapter 11 Two-sample Tests of HypothesisGOALSpaired dependent observationsGOALSdependent independent samplesComparing two populations – Some ExamplesComparing two populations – Some ExamplesComparing two populations – Some Examples (continued)Comparing Two Population Means of Independent Samples22212121n n X X z σσ+-=Comparing Two Population Means of Independent SamplesComparing Two Population Means of Independent Samples – Examplemean checkout timeis longerComparing Two Population Means of Independent Samples – ExampleExample continued Step 1:1Step 2:Step 3:Example continued Step 4:Step 5: Compute the value of z and make a decisionExample continued 13.3064.02.010030.05040.03.55.52222==+-=+-=uu s s us n n X X z σσExample continued Step 5:Two-Sample Tests about ProportionsTwo-Sample Tests about ProportionsTwo-Sample Tests about ProportionsTwo Sample Tests of ProportionsTwo-Sample Tests of Proportions continuedTwo Sample Tests of Proportions - Examplethere is a difference in the proportions of younger and olderTwo Sample Tests of Proportions - ExampleTwo Sample Tests of Proportions - Example Step 1:01 2112difference12Two Sample Tests of Proportions - Example Step 2:Two Sample Tests of Proportions - Example Step 3:Step 4:Two Sample Tests of Proportions - Example Step 5:Two Sample Tests of Proportions - ExampleTwo Sample Tests of Proportions – Example (Minitab Solution)Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test)Small sample test of means continued2)1()1(212222112-+-+-=n n s n s n s p ⎪⎪⎭⎫ ⎝⎛+-=2122111n n s X X t pComparing Population Means with Unknown Population Standard Deviations (the Pooled t-test)Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test)Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test)Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - Example Step 1:01 2112Step 2:Step 3:Step 4:012-2 12-2Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - ExampleComparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - Example Step 5:(a) Calculate the sample standard deviationsStep 5:Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - Example -0.662Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - Example Step 5:not to reject the nullhypothesis-0.662 falls in the regionbetween -1.833 and 1.833no differenceComparing Population Means with Unknown Population Standard Deviations (the Pooled t-test) - ExampleTwo-Sample Tests of Hypothesis: Dependent SamplesDependent samples paired related in some fashionHypothesis Testing Involving Paired Observationstd s nd/dependentHypothesis Testing Involving Paired Observations - ExampleHypothesis Testing Involving Paired Observations - ExampleHypothesis Testing Involving Paired Observations - ExampleStep 1:1Step 2:Step 3:Step 4:Hypothesis Testing Involving PairedObservations - ExampleStep 5:Hypothesis Testing Involving PairedObservations - ExampleThe computed value of t isgreater than the highercritical value, so ourdecision is to reject thethat there is a difference inthe homes.Hypothesis Testing Involving Paired Observations – Excel Example。
商务与经济统计01
• 还有一些公司专门从事通过Internet出售数据的业务。
数据来源
统计研究
• 统计研究可以分为实验性统计研究和观察性统计研
究。
• 在实验性统计研究中，首先确定要研究的变量，然
后通过控制其它一个或多个因素，观察这些因素的 改变对变量产生的影响。例如对药物效果的实验性 研究。
• 在观察性研究（或称为非实验性研究）中，不对要
海珠保险公司的总经理希望了解上个月每份保单 的金额分布情况。他随机抽查了50份保单，每份保单 的金额如下（单位：百元）：
91 78 93 57 75 52 99 80 97 62 71 69 72 89 66 75 79 75 72 76 104 74 62 68 97 105 77 65 80 109 85 97 88 68 83 68 71 69 67 74 62 82 98 101 79 105 79 69 62 73
测度量表
间隔量表
• 间隔量表与系数量表相类似，但间隔量表的每个数
据项之间的间隔相等。
• 间隔量表的数据只能用数字表示。
测度量表
间隔量表
• 举例:
小强考TOEFL考了580分，旺财考TOEFL考了 620分。旺财比小强多考了40分。
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Chapter 1
数据与统计学
本章主要内容
统计学在商务和经济中的应用 数据 数据来源 描述性统计 统计推断
统计学在商务与经济中的应用
会计 会计师事务所在进行审计的时候需要利用抽样技术进 行选择性审计。 金融 金融分析师利用一系列的统计数据，例如市赢率、每 股收益等，来进行投资分析。 市场营销 在新产品上市前，利用对消费者的抽样调查了解市场 前景；利用POS机上的销售数据，进行产品的市场分 析与研究。