Business Statistics
Business Statistics
1000+ 人选课
更新日期:2026/04/03
开课时间2026/02/06 - 2026/07/23
课程周期24 周
开课状态开课中
每周学时-
课程简介

Overview

This course aims to introduce common data analysis techniques that are used in business world. Although for typical applications you will learn how to use calculators or Microsoft Excel to perform the calculations associated with these techniques, the focus of this course however is on how to analyze and interpret the statistical results or the outputs from Excel. You will learn how to apply these techniques by working with examples that are relevant to most major business disciplines and the functional areas in large organizations, including Accounting (particularly Auditing), Economics, Finance, Financial Planning, Human Resource Management, Information Technology, Logistics and Transport and Marketing.

Learning Outcomes

Upon successful completion of this course, it is expected that you will have acquired the following course specific learning outcomes.

1. Present and describe statistical information using a wide range of numerical and graphical procedures.

2. Use of technical tools such as Excel to obtain both the numerical and graphical outputs from data.

3. Understand and apply sample statistics to arrive at probable conclusions about the target population that affect business decisions.

4. Conduct estimation and hypothesis testing using your knowledge of probability theory and resolve problems.

5. Use regression and correlation analysis to describe relationships between variables and to produce forecasts of the future values of strategic variables that reflect on experiences learned in your studies.

6. Produce solutions to practical problems that encourage intellectual openness and curiosity towards the development of skills that can be used in real life situations.

7. Enable you to present quantitative information at a professional level that would meet client expectations.

Prescribed Textbook

Levine, D.M., Krehbiel, T.C., Berenson, M.L. (2016). Business Statistics: A First Course. 7th ed. Pearson.


课程大纲
ch01-Introduction and Data Collection
ch01.1-Introduction
ch01.2-Types of data
ch02-Presenting Data in Tables and Charts
ch02.1-Organizing Numerical Data
ch02.2-Organizing Categorical Data
ch03-Numerical Descriptive Measures
ch03.1-Measures of central tendency
ch03.2-Measures of variation
ch03.3-Z score and emperical rule
ch03.4-Shape
ch04-Basic Probability
ch04.1-Basic Probability Concepts
ch04.2-Conditional Probability
ch04.3-Bayes' Theorem
ch05-Discrete Probability Distributions
ch05.1-The probability Distribution for a discrete random variable
ch05.2-Binomial Distribution
ch05.3-Hypergeometric Distribution and Poisson Distribution
ch06-The Normal Distribution
ch06.1-Standard Normal Distribution
ch06.2-Finding probability in a normal distribution
ch06.3-Assessing Normality
ch07-Sampling and Sampling Distributions
ch07.1-Types of sampling methods
ch07.2-Sampling distribution of the mean
ch07.3-Sampling distribution of the proportion
ch08-Confidence Interval Estimation
ch08.1-Confidence interval estimation for the mean-sigma known
ch08.2-Confidence interval estimation for the mean-sigma unknown
ch08.3-Confidence interval estimation for the proportion
ch08.4-Determing sample size
ch09-Fundamentals of Hypothesis Testing: One Sample Tests
ch09.1-Fundamentals of Hypothesis Testing Methodology
ch09.2-Test of Hypothesis about a population mean
ch09.3-Test of Hypothesis about a population proportion
ch10-Two Sample Tests and One Way ANOVA
ch10.1-Comparing the Means of two independent populations
ch10.2-Comparing the Means of two related populations
ch10.3-Comparing the proportions of two independent populations
ch10.4-F test for the difference between two variances
ch10.5-One-Way analysis of variance
ch11-Simple Linear Regression
ch11.1-Determining the simple linear regression equation
ch11.2-Measures of variation
ch11.3-Residual analysis and inferences about regression coefficients
ch11.4-Pitfalls in regression
Final Exam
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