Introductory Business Statistics

Explores the basic ideas behind statistics, such as populations, samples, the difference between data and information, and most importantly sampling distributions.

**Tag(s):**
Statistics

**Publication date**: 01 Dec 2010

**ISBN-10**:
n/a

**ISBN-13**:
n/a

**Paperback**:
82 pages

**Views**: 6,562

**Type**: Textbook

**Publisher**:
Global Text Project

**License**:
Creative Commons Attribution-ShareAlike 4.0 International

**Post time**: 04 May 2017 07:00:00

Introductory Business Statistics

Explores the basic ideas behind statistics, such as populations, samples, the difference between data and information, and most importantly sampling distributions.

You are free to:

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material for any purpose, even commercially.

The licensor cannot revoke these freedoms as long as you follow the license terms.

Click**here** to read the full license.

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material for any purpose, even commercially.

The licensor cannot revoke these freedoms as long as you follow the license terms.

Click

Excerpts from the Preface:

Thomas K. Tiemann wrote:I have been teaching introductory statistics to undergraduate economics and business students for almost 30 years. When I took the course as an undergraduate, before computers were widely available to students, we had lots of homework, and learned how to do the arithmetic needed to get the mathematical answer. When I got to graduate school, I found out that I did not have any idea of how statistics worked, or what test to use in what situation. The first few times I taught the course, I stressed learning what test to use in what situation and what the arithmetic answer meant.

As computers became more and more available, students would do statistical studies that would have taken months to perform before, and it became even more important that students understand some of the basic ideas behind statistics, especially the sampling distribution, so I shifted my courses toward an intuitive understanding of sampling distributions and their place in hypothesis testing. That is what is presented here — my attempt to help students understand how statistics works, not just how to "get the right number".

Tweet

About The Author(s)

Thomas K. Tiemann is Jefferson Pilot Professor of Economics at Elon University in North Carolina, USA. He earned an AB in Economics at Dartmouth College and a PhD at Vanderbilt University. He has been teaching basic business and economics statistics for over 30 years, and tries to take an intuitive approach, rather than a mathematical approach, when teaching statistics.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors