Quick & Easy Statistics: A Practical and Interactive Approach Using SPSS

Statistics for Researchers Who Need to Get Moving

Statistics can feel like a gatekeeper in research: necessary, intimidating, and often taught with more theory than a busy project can absorb. Quick & Easy Statistics takes a different route. Written by Fatai Akemokwe, this practical guide uses IBM SPSS Statistics as the working tool and keeps the statistical background concise enough to support action rather than delay it. The aim is not to turn readers into career statisticians. It is to help them handle their own data with confidence and choose analyses that fit their research questions.

From Data Entry to a Clean SPSS Workspace

The early chapters set the foundation. You’ll meet essential statistical terms, learn how variable types shape later choices, and see how to enter data directly into SPSS or import it from other sources. The book also walks through the SPSS interface, altering data entries, copying and pasting, inserting new cases or variables, computing new variables, recoding, handling multiple-response data, and selecting or filtering cases. These are the unglamorous tasks that decide whether an analysis runs smoothly later.

Exploring, Describing, and Understanding Your Data

Before inferential tests enter the picture, the book turns to description and exploration. Frequencies and descriptives give a first view of the dataset. Assessments of normality help determine whether parametric assumptions are reasonable. Crosstabulations and correlations reveal relationships and patterns. This section matters because good analysis is rarely about running the most complicated test; it is about knowing what the data look like first.

Choosing the Right Test—and Running It in SPSS

Inferential statistics can be where uncertainty takes over. The book addresses that with a chapter on choosing an appropriate test, then demonstrates common procedures step by step. Readers encounter the one-sample t-test, independent-samples t-test, paired-samples t-test, one-way analysis of variance, chi-square and risk, correlation, and linear regression. Each method is tied to practical research situations rather than presented as an abstract calculation.

Regression, Agreement, and Diagnostic Accuracy

The later chapters extend into areas that many introductory texts leave out. Binary logistic regression is covered for outcomes that are categorical rather than continuous. Tests of agreement and tests of diagnostic accuracy are included, along with receiver operating characteristics (ROC) curves. For researchers working with screening tools, clinical measures, or classification problems, these chapters connect statistical output to real decisions.

Survival Analysis with Kaplan-Meier and Cox Models

A final substantial section addresses survival analysis. Kaplan-Meier analysis and Cox proportional hazards modelling are introduced in the same practical style, giving readers a route into time-to-event data without requiring a separate advanced biostatistics course first.

Who Will Find This Useful

This book is aimed at aspiring researchers, students, and professionals who need to analyse data with SPSS and want a focused, interactive guide. It suits readers who prefer succinct theoretical grounding alongside hands-on procedures. The book notes that IBM SPSS Statistics 22 was the latest version at the time of writing, while also observing that version differences have not altered the basic process of using the software for analysis. Sample data files are used throughout to support practice.

A Focused Companion for Real Research

Quick & Easy Statistics keeps its promises modest and useful: essential theory, clear SPSS steps, and a path through the tests researchers most often need. For anyone who has felt stuck between a statistics textbook and a software manual, this guide offers a practical middle ground.