Business Statistics

Data is everywhere in business world. How to deal with the data and extract useful information from the data would be very important for decision-making. The purpose of this course is to give you, especially those in the fields of finance, management and economics and those who want to be expert in data analysis, an introduction to the fields of statistics and its applications in business. Business Statistics will help you understand the business world much more deeply.

开设学校:上海对外经贸大学;学科:经济学、

Business Statistics课程:前往报名学习

Business Statistics视频慕课课程简介:

Data is everywhere in business world. How to deal with the data and extract useful information from the data would be very important for decision-making. The purpose of this course is to give you, especially those in the fields of finance, management and economics and those who want to be expert in data analysis, an introduction to the fields of statistics and its applications in business. Business Statistics will help you understand the business world much more deeply.

前往报名学习

Business Statistics课程列表:

{{'上次学习:'+learn_list['1227370fu042801intl']['last_leaf_name']}}

ch01-Introduction and Data Collection

-ch01.1-Introduction

--ch01.1-Introduction

--Exercise-chap1.1

-ch01.2-Types of data

--ch01.2-Types of data

--Exercise-chap01.2

ch02-Presenting Data in Tables and Charts

-ch02.1-Organizing Numerical Data

--ch02.1.1-Organizing numerical variables-1

--ch02.1.2-Organizing numerical variables-2

--Exercise-ch02.1

-ch02.2-Organizing Categorical Data

--ch02.2-Organizing categorical variables

--Exercise-ch02.2

ch03-Numerical Descriptive Measures

-ch03.1-Measures of central tendency

--ch03.1.1-Measures of central tendency

--ch03.1.2-Percentiles and Z score

--Exercise-ch03.1

-ch03.2-Measures of variation

--ch03.2-Measures of variation

--Exercise-ch03.2

-ch03.3-Z score and emperical rule

--ch03.3-Emperical rule and Z score

--Exercise-ch03.3

-ch03.4-Shape

--ch03.4-Shape

--Exercise-ch03.4

ch04-Basic Probability

-ch04.1-Basic Probability Concepts

--Exercise ch04-01

--ch04.1.1-Basic probability concepts

--ch04.1.2-Basic probability concepts-2

-ch04.2-Conditional Probability

--Exercise-ch04-02

--ch04.2-Conditional Probability

-ch04.3-Bayes' Theorem

--Exercise ch04.3

--ch04.3-Bayes' Theorem

ch05-Discrete Probability Distributions

-ch05.1-The probability Distribution for a discrete random variable

--ch05.1.1-The probability distribution for a discrete random variable

--ch05.1.2-Expected Value and Variance

--Exercise ch05.1

-ch05.2-Binomial Distribution

--ch05.2-Binomial distribution

--Exercise ch05.2

-ch05.3-Hypergeometric Distribution and Poisson Distribution

--ch05.3.1-Hypergeometric distribution

--ch05.3.2-Poisson Distribution

--Exercise ch05.3

ch06-The Normal Distribution

-ch06.1-Standard Normal Distribution

--Exercise ch06.1

--ch06.1.1-Standard Normal Distribution

--ch06.1.2-How to Use the Normal Distribution Table

-ch06.2-Finding probability in a normal distribution

--Exercise ch06.2

--ch06.2.1-Find probability in a normal distribution

--ch06.2.2-Normal Distribution-an Example

-ch06.3-Assessing Normality

--Exercise ch06.3

--ch06.3-Assessing Normality

ch07-Sampling and Sampling Distributions

-ch07.1-Types of sampling methods

--ch07.1.1-Types of sampling methods-1

--ch07.1.2-Types of sampling methods-2

--Exercise ch07.01

-ch07.2-Sampling distribution of the mean

--ch07.2.1-Sampling distribution of the mean

--ch07.2.2-Sampling distribution of the mean-an Example

--Exercise-ch07.2

-ch07.3-Sampling distribution of the proportion

--ch07.3.1-Sampling distribution of the proportion

--ch07.3.2-Sampling distribution of the proportion-Example

--Exercise ch07.3

ch08-Confidence Interval Estimation

-ch08.1-Confidence interval estimation for the mean-sigma known

--ch08.1-Condidence interval estimation for the mean-sigma known

--Exercise ch08.1

-ch08.2-Confidence interval estimation for the mean-sigma unknown

--ch08.2.1-Confidence interval for the mean-sigma unknown

--ch08.2.2-Confidence interval estimatin for the mean-sigma unknown-an example

--Exercise ch08.2

-ch08.3-Confidence interval estimation for the proportion

--ch08.3-Confidence interval estimation for proportion

--Exercise ch08.3

-ch08.4-Determing sample size

--ch08.4.1-Sample size determination for the mean

--ch08.4.2-Determing sample size for the proportion

--Exercise ch08.4

ch09-Fundamentals of Hypothesis Testing: One Sample Tests

-ch09.1-Fundamentals of Hypothesis Testing Methodology

--ch09.1.1-Introduction to Hypothesis testing

--ch09.1.2-Type I and Type II error

--Exercise-ch09.1

-ch09.2-Test of Hypothesis about a population mean

--ch09.2.1-Critical valule approach

--ch09.2.2-P value approach

--ch09.2.3-One tail test

--ch09.2.4-T test of Hypothesis for the mean (sigma unknown)

--Exercise ch9.2

-ch09.3-Test of Hypothesis about a population proportion

--ch09.3-Z Test of Hypothesis for the proportion

--Exercise ch09.3

ch10-Two Sample Tests and One Way ANOVA

-ch10.1-Comparing the Means of two independent populations

--ch10.1.1-Comparing the differences between two means-Z test

--ch10.1.2-Pooled variance T test

--ch10.1.3-Pooled variance T test_an example

--ch10.1.4-Separate variance T test

--Exercise 10.1

-ch10.2-Comparing the Means of two related populations

--ch10.2-Paired T test

--Exercise ch10.2

-ch10.3-Comparing the proportions of two independent populations

--ch10.3-Comparing the proportions of two independent populations

--Exercise ch10.3

-ch10.4-F test for the difference between two variances

--ch10.4-F test for the ration of two variances

--Exercise ch10.4

-ch10.5-One-Way analysis of variance

--Exercise ch10.5

--ch10.5.1-One way ANOVA-Theory

--ch10.5.2-One way ANOVA-Example

--ch10.5.3-The Tukey Kramer Procedure

--ch10.5.4-Levene's test for homogeneity of variances

ch11-Simple Linear Regression

-ch11.1-Determining the simple linear regression equation

--ch11.1.1-Introduction to simple linear regression model

--ch11.1.2-Least squares method

--Exercise ch11.1

-ch11.2-Measures of variation

--ch11.2-Measures of variation

--Exercise ch11.2

-ch11.3-Residual analysis and inferences about regression coefficients

--ch11.3.1-Residual analysis

--ch11.3.2-Inferences about regression coefficients

--Exercise ch11.3

-ch11.4-Pitfalls in regression

--ch11.4-Pitfalls in regression

--Exercise ch11.4

Final Exam

-Final Exam

Business Statistics开设学校:上海对外经贸大学

Business Statistics授课教师:

雷平-讲师-上海对外经贸大学-

上海对外经贸大学教师,主讲过十多轮《商务统计(英)》《概率论与数理统计》《统计学(英)》《统计软件》等课程。美国佐治亚州立大学访问学者(2012)、加拿大阿尔伯塔大学访问学者(2017)。主持上海市全英语示范课程《商务统计》(2013-2016),并获得“上海市全英语教学示范课程”荣誉称号;主持上海市留学生全英语示范课程《商务统计》(2015-2017),并获得“上海市留学生全英语教学示范课程”荣誉称号;主编《概率论与数理统计》教材两本(清华大学出版社2018,立信会计出版社2016),翻译Anderson的经典统计教材《商务与统计统计》两本(机械工业出版社2018,2015)。获得过上海市青年教师教学竞赛三等奖(自然科学组,2016年)、上海对外经贸大学教学标兵(2012)、上海对外经贸大学全英语教师教学质量奖(2011年)、上海对外经贸大学青年教师教学质量奖(2008)。

刘永辉-教授-上海对外经贸大学-

华东师范大学理学博士,教授,统计学博士生导师。教育部统计学类专业教学指导委员会委员(2018-2022),中国对外经济贸易统计学会学术委员会副主任,中国管理科学与工程学会金融计量与风险管理研究会常务理事,中国现场统计研究会资源与环境分会常务理事等职务。担任全国经济与管理类统计学系列教材编委会编委,入选上海市人才发展资金计划。研究领域为统计诊断、金融计量和贸易统计。在国内外重要学术期刊上公开发表学术论文90多篇, 其中SCI检索论文20多篇、CSSCI检索论文多篇。主讲《商务统计(英)》《应用时间序列分析》和《数理金融》,先后培养博士生、硕士生40余名。获得上海市优秀教学成果二等奖、宝钢教育基金会优秀教师奖、上海市育才奖以及中国金融教育先进工作者等荣誉。

赵倩-副教授-上海对外经贸大学-

澳大利亚麦考瑞大学应用金融和精算学博士,统计与信息学院副教授、硕士生导师。曾任麦考瑞大学、香港大学、墨尔本大学访问学者。2016年入选上海市青年东方学者。赵倩一直致力于数学与保险、金融等交叉学科问题的研究以及统计学相关课程的教学工作。主讲本科生课程《统计学(英)》《商务统计(英)》《金融统计(选)》,研究生课程《风险管理》《经济时间序列分析》等,2017年荣获校级全英语教师教学质量奖。 主持国家自然科学基金面上项目、青年项目各一项,省部级项目一项。已在国际同行审阅的杂志上共发表SSCI、SCI学术论文十余篇,其中,以第一作者身份在精算学顶级杂志Insurance: Mathematics and Economics以及管理运筹类著名杂志 European Journal of Operational Research上共发表学术论文3篇。

郝程程-副教授-上海对外经贸大学-

瑞典斯德哥尔摩大学统计学博士,副教授,硕士生导师。曾任美国马里兰大学数学与统计系、美国德克萨斯大学管理科学与统计系访问学者。中国现场统计研究会大数据统计分会理事。2016年入选上海高校青年东方学者、上海市浦江人才。 主讲课程《统计学(英)》《探索性数据分析(英)》《描述统计学(英)》《广义线性模型》等。 研究领域为多元纵向数据分析与异常点识别领域,在《Scandinavian Journal of Statistics》《Statistical Methods in Medical Research》等SCI期刊发表第一作者论文6篇;主持国家自然科学基金项目1项,省部级项目2项,瑞典皇家科学院项目2项。

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