Linear regression analysis, with its many generalizations, is the predominant quantitative method used throughout the social sciences and beyond. The goal of the method is to study relations among variables. In this book, Schoon, Melamed and Breiger turn regression modeling inside out to put the emphasis on the cases (people, organizations, and nations) that comprise the variables. By re-analyzing influential published research, they reveal new insights and present a principled way to unlo...

This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata, SPSS and SAS, to using R, and this book uses statistical models which...

Not knowing statistics can lead to a loss of money, time, and accurate information.What am I looking at? What do these numbers mean? Why? These are frequent thoughts of those who don't know much about statistics."I'm not a number's person" is not a good excuse to avoid learning the basics of this essential skill. Are you a person who earns money? Do you shop at the supermarket? Do you vote? Do you read the news? I'm sure you do.Learn to make...

David de Vaus' classic text Surveys in Social Research provides clear advice on how to plan, conduct and analyse social surveys. It emphasises the links between theory and research, the logic and interpretation of statistics and the practices of social research. This sixth edition has been completely revised and updated, and contains new examples, data and extensive lists of web resources.As well as explaining how to conduct good surveys, de Vaus shows how to become a crit...

Econometrics: A Simple Introduction offers an accessible guide to the principles and methods of econometrics, with data samples, regressions, equations and diagrams to illustrate the analysis.Examine a linear and multiple regression model, ordinary least squares method, and the Gauss-Markov conditions for a best linear unbiased estimator.Understand hypothesis testing, with a null hypothesis, t, F or chi-square test statistics and distributions, and interpret regression resu...

While Applying Social Statistics is "about" social statistics and includes all of the topics generally covered in similar texts, it is first and foremost a book about how sociologists use statistics. Its emphasis is on statistical reasoning in sociology and on showing how these principles can be applied to numerous problems in a wide variety of contexts; to answer effectively the question "what's it for."A main learning objective is to help students understand how and why ...

This text gives budding actuaries and financial analysts a foundation in multiple regression and time series. They will learn about these statistical techniques using data on the demand for insurance, lottery sales, foreign exchange rates, and other applications. Although no specific knowledge of risk management or finance is presumed, the approach introduces applications in which statistical techniques can be used to analyze real data of interest. In addition to the fundamentals, this boo...

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills i...

This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using RStudio and reproducible research examples. It will enable students to use R for data cleaning, data visualization and quantitative model building using statistical methods like linear regression, econometrics (GARCH etc), Copulas, ...

This fully updated edition of Statistics for Research explains statistical concepts in a straight-forward and accessible way using practical examples from a variety of disciplines. If you′re looking for an easy-to-read, comprehensive introduction to statistics with a guide to SPSS, this is the book for you!The new edition features:- Clear explanations of all the main techniques of statistical analysis- A brand new student-friendly, easy-to-navigate design- E...

The individual risks faced by banks, insurers, and marketers are less well understood than aggregate risks such as market-price changes. But the risks incurred or carried by individual people, companies, insurance policies, or credit agreements can be just as devastating as macroevents such as share-price fluctuations. A comprehensive introduction, The Econometrics of Individual Risk is the first book to provide a complete econometric methodology for quantifying and managing this ...

Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications...