Quantitative Analysis and IBM® SPSS® Statistics
A Guide for Business and Finance

Authors: Abdulkader Aljandali



Utilizes the popular and accessible IBM SPSS Statistics software package to teach data analysis for business and finance in a step-by-step approach

A comprehensive, in-depth guide, especially relative to the competition

Explains the statistical assumptions and rationales underpinning application of the SPSS package, instead of simply presenting techniques

More than 100 color graphs and figures

Includes directed download of the software IBM SPSS Statistics 22.

This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods.

IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, GSK, TfL, the NHS, Shell, Unilever, and W.H.S.

Although the emphasis in this guide is on applications of IBM SPSS Statistics, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the package; therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum.

Table of contents

Front Matter

Introduction to IBM SPSS Statistics
• Front Matter
• Getting Started

Data Examination and Description
• Front Matter
• Graphics and Introductory Statistical Analysis of Data
• Frequencies and Crosstabulations
• Coding, Missing Values, Conditional and Arithmetic Operations

Hypothesis Tests
• Front Matter
• Hypothesis Tests Concerning Means
• Nonparametric Hypothesis Tests

Methods of Business Forecasting
• Front Matter
• Bivariate Correlation and Regression
• Elementary Time Series Methods

Other Useful Features of IBM SPSS Statistics
• Front Matter
• Other Useful Features of IBM SPSS Statistics
• Secondary Sources of Data for Business, Finance and Marketing Students

Back Matter

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