This award-winning book combines humor with step-by-step instruction to make statistics and IBM SPSS accessible, covering topics from basic theory to advanced techniques such as regression, factor analysis, and multilevel modeling. It includes real-world data, practice activities, and guidance on common statistical errors, making it suitable for students across a wide range of disciplines and learning environments. Updated for the latest version of IBM SPSS Statistics, the book also features an extensive online resource with videos, case studies, datasets, and test banks that can be integrated into virtual learning platforms to support teaching, assessment, and project work.

Uploaded July 2026

There are, very few up-to-date resources by which graduate students and researchers in biology can familiarize themselves with the key methodologies of applied statistics as they specifically connect to the applied life sciences. Applied Statistics in Biology remedies this oversight with a thorough, accessible overview to statistics and its biological applications.

Uploaded May 2026

Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications will serve as a solid advanced reference for researchers, scientists, engineers and advanced students who wish to implement practical tasks through clustering formulations.

Uploaded May 2026

Misinformation, disinformation, and fake news abound and it's increasingly difficult to know what's true. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data.

Uploaded May 2026

This book explores how mathematical concepts of "sameness" and "difference" can be applied to real-life social, emotional, and logical issues. It challenges the rigid definition of equality, arguing that almost anything can be considered both equal and unequal depending on perspective, providing a new framework for understanding fairness and complexity.

Uploaded March 2026

Take a deeper dive into understanding the five practices―anticipating, monitoring, selecting, sequencing, and connecting―for facilitating productive mathematical conversations in your elementary classrooms and learn to apply them with confidence. This follow-up to the modern classic, Five Practices for Orchestrating Productive Mathematics Discussions, shows the five practices in action in Grades K-5 classrooms and empowers teachers to be prepared for and overcome the challenges common to orchestrating math discussions.

Uploaded October 2025

An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods.

Uploaded October 2025

Designed for researchers and students without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in psychology and the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data.

Uploaded October 2025

The second edition of Time Series: A Biostatistical Introduction is an introductory account of time series analysis, written from the perspective of applied statisticians whose interests lie primarily in the biomedical and health sciences. This edition has a stronger focus on substantive applications, in which each statistical analysis is directed at a specific research question. Separate chapters cover simple descriptive methods of analysis, including time-plots, smoothing, the correlogram and the periodogram; theory of stationary random processes; discrete-time models for single series; continuous-time models for single series; generalized linear models for time series of counts; models for replicated series; spectral analysis, and bivariate time series.

Uploaded October 2025

This book develops a framework to analyze algorithmic aspects of discrete choice models in convex optimization. The central aspect is to derive new prox-functions from discrete choice surplus functions, which are then incorporated into convex optimization schemes. The book provides further economic applications of discrete choice prox-functions within the context of convex optimization such as network manipulation based on alternating minimization and dynamic pricing for online marketplaces.

Uploaded October 2025