Statistical Package for the Social Sciences, or SPSS, is a software package widely used for statistical analysis in social science research and various other fields. It provides a comprehensive set of tools for data preparation, statistical analysis, and data visualization.
Initially developed by IBM, SPSS has become one of the most popular statistical software packages due to its user-friendly interface and robust analytical capabilities.
Some notable features of SPSS include:
- Data management: SPSS allows users to import, clean, and manage datasets. Users can enter data directly into SPSS or import data from various file formats, such as Excel, CSV, or databases.
- Descriptive Statistics: SPSS provides various tools for calculating descriptive statistics like measures of central tendency, frequency distribution and dispersion, helping researchers explore and summarize their data’s main characteristics.
- Inferential statistics: SPSS supports various inferential statistical analyses, including t-tests, ANOVA (Analysis of Variance), regression analysis, and chi-square tests, among others. These analyses help researchers draw conclusions about populations based on sample data.
- Data visualization: SPSS offers graphical tools for data visualization, including charts, histograms, and scatter plots. Visualizations aid in interpreting patterns and trends within the data.
- Advanced analytics: Besides primary statistical analyses, SPSS provides capabilities for more advanced analytics, such as factor analysis, cluster analysis, and logistic regression.
- Integration with other software: SPSS is designed to work seamlessly with other software tools. It supports integrating databases, spreadsheet programs, and additional data analysis and reporting tools.
SPSS is widely used in academic research, market research, healthcare, and various industries where statistical analysis is essential. While it has traditionally been associated with social sciences, its versatility and broad range of statistical procedures make it applicable to various disciplines.
List of recommended resources #
For a broad overview #
This video tutorial by Data for Development on YouTube gives a brief introduction to SPSS, along with the steps to enter and analyze data using the software.
This brief overview of the IBM SPSS Statistics Software gives a quick description of the main features of SPSS and the basic steps of opening and saving data files.
For in depth understanding #
Written by Andy Field, this book provides a step=by-step instruction to various functions in SPSS software: from theory to factor analysis, regression and multilevel modeling, all presented in an accessible and humorous fashion. The book also covers various versions of IBM SPSS Statistics.
This video tutorial by Data for Development on YouTube gives an in-depth lesson on using SPSS, understanding data and variables, and interpreting and reporting summary statistics.
This book by Perry R. Hinton, Isabella McMurray, and Charlotte Brownlow uses IBM SPSS version 21. Its chapters provide an introduction to binary logistic regression, explain bootstrapping, as well as cover some new features like the chart builder.
Case study #
This research article, written by Daniel T. L. Shek and Cecilia M. S. Ma, describes the procedures for performing analyses based on LMM (linear mixed models) in SPSS. The procedures are demonstrated through the findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong.
This article by Brian P. O’connor describes efficient and brief programs for using SAS and SPSS to conduct the MAP test and parallel analyses.