IBM SPSS Statistics Tutorial – Part 01 – Introduction

Let’s begin by explaining the abbreviations:

IBM stands for International Business Machines Corporation. It is an American multinational technology corporation headquartered in Armonk, New York, and operates in over 175 countries.

SPSS originally stood for Statistical Package for the Social Sciences, reflecting its original market. Later on, it was changed to Statistical Product and Service Solutions.
SPSS was initially released in 1968 as the Statistical Package for the Social Sciences, after being developed by Norman H. Nie, Dale H. Bent, and C. Hadlai Hull. These principals later incorporated as SPSS Inc. in 1975. On July 28, 2009, SPSS Inc. announced that it was being acquired by IBM for US$1.2 billion.

Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It involves methods and techniques for gathering, summarizing, and analyzing numerical information to make informed decisions and draw meaningful conclusions. Statistics plays a crucial role in various fields, including social sciences, economics, business, medicine, and many others, providing tools and insights for understanding patterns, relationships, and trends within data sets.

SPSS is licensed software, and you need to purchase a license for it. The software is available in different variants, including Base, Standard, Professional, or Premium versions. Alternatively, you can also opt for a subscription-based model. You can view the pricing details here:

SPSS software is primarily designed for quantitative data analysis and may not be suitable for qualitative data analysis.

The first version of SPSS was SPSS 1, released in 1968. The latest version of SPSS is SPSS 29, which was released in September 2022. Upon opening the SPSS software, the version number is displayed on the splash screen. For this tutorial, I will be using SPSS version 26, released in 2018.. If you wish to try out SPSS, you can install the trial version of SPSS 29 from the official IBM website. The trial version will remain active for 30 days and will install the Desktop edition for both Windows and Mac platforms. You can download the trial version from the following link:

You can view the version history at this Wikipedia Link:

You can watch how to install the trail version here:

On my website, I have categorized all SPSS-related posts under the category ‘SPSS.’ To view all posts related to SPSS, simply click on the following link:

The most renowned website for learning SPSS is Laerd Statistics, which offers nearly 100 statistical guides covering various tests and features. You can explore all the available features and tests on the website through the link below. To access all the features, a user must obtain a subscription and license; however, there are also many free learning resources available. Please note that the subscription is not currently available for users in Pakistan.

I have also included links to various statistical tests available on Laerd Statistics in the following blog post:

In the SPSS software, you will also find the Help option in the main menu. When you click on Help, you will be presented with the options of Topics and Tutorial. You can also learn SPSS through this official help provided by IBM. The online help for various versions can also be accessed here:

There are also other software options available for statistical analysis that offer similar functionalities to SPSS. Some notable names include:

  • Stata is a statistical software package that provides a range of data analysis and management tools.
  • R is a free and open-source programming language and software environment for statistical computing and graphics.
  • SAS is a software suite for advanced analytics, business intelligence, and data management.
  • JMP is a statistical discovery software developed by SAS.
  • Minitab is a statistical software package primarily used for quality improvement and Six Sigma applications.
  • Python is a versatile programming language, and it can be used for statistical analysis with the help of various libraries such as NumPy, pandas, and SciPy.

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