Using Stata for Quantitative Analysis is an applied, self-teaching resource. It is written in such a way that a reader with no experience with statistical software can sit down and be working with data in a very short amount of time. The author proposes to teach the language of Stata from an intuitive perspective, furthering students’ overall retention, using many screen shots from Stata to guide students.
Using Stata for Quantitative Analysis, Second Edition offers a brief, but thorough introduction to analyzing data with Stata software. It can be used as a reference for any statistics or methods course across the social, behavioral, and health sciences since these fields share a relatively similar approach to quantitative analysis. In this book, author Kyle Longest teaches the language of Stata from an intuitive perspective, furthering students’ overall retention and allowing a student with no experience in statistical software to work with data in a very short amount of time. The self-teaching style of this book enables novice Stata users to complete a basic quantitative research project from start to finish. The Second Edition covers the use of Stata 13 and can be used on its own or as a supplement to a research methods or statistics textbook.
Statistics is a branch of mathematics that studies variability, as well as the random process that generates it, following laws of probability. This book provides over 2,000 Exam Prep questions and answers to accompany the text Using Stata for Quantitative Analysis Items include highly probable exam items: Evidence-based practice, Randomized experiment, role, principles, repeated measures, Normal distribution, Standard error, Definition, Internet, sampling distribution, f-test, understanding, and more.
Vital Statistics: an introduction to health science statistics e-book is a new Australian publication. This textbook draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student. It demonstrates how an understanding of statistics is useful in the real world, as well as in statistics exams. Vital Statistics: an introduction to health science statistics e-book is a relatively easy-to-read book that will painlessly introduce or re-introduce you to the statistical basics before guiding you through more demanding statistical challenges. Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics. It explores: How data relates to information, and how information relates to knowledge How to use statistics to distinguish information from disinformation The importance of probability, in statistics and in life That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be How to appropriately apply and interpret statistical measures of difference and association How qualitative and quantitative methods differ, and when it’s appropriate to use each The special statistical needs of the health sciences, and some especially health science relevant statistics The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability. Reader-friendly writing style t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.
This book is an easily accessible and comprehensive guide which helps make sound statistical decisions, perform analyses, and interpret the results quickly using Stata. It includes advanced coverage of ANOVA, factor, and cluster analyses in Stata, as well as essential regression and descriptive statistics. It is aimed at those wishing to know more about the process, data management, and most commonly used methods in market research using Stata. The book offers readers an overview of the entire market research process from asking market research questions to collecting and analyzing data by means of quantitative methods. It is engaging, hands-on, and includes many practical examples, tips, and suggestions that help readers apply and interpret quantitative methods, such as regression, factor, and cluster analysis. These methods help researchers provide companies with useful insights.
Financial Econometrics Using Stata is an essential reference for graduate students, researchers, and practitioners who use Stata to perform intermediate or advanced methods. After discussing the characteristics of financial time series, the authors provide introductions to ARMA models, univariate GARCH models, multivariate GARCH models, and applications of these models to financial time series. The last two chapters cover risk management and contagion measures. After a rigorous but intuitive overview, the authors illustrate each method by interpreting easily replicable Stata examples.
"Quantitative Data Analysis, by Donald J. Treiman, is a well-written demonstration of how to answer questions using statistics. The range of techniques is broad, ranging from simple advice for making tables readily readable through linear and logistic regression to log-linear and random-effects models ... Treiman writes using clear, precise language ... Treiman also takes the time and effort to explain how to avoid common pitfalls of data analysis ... worth a look for those wanting to see the applications of a wide variety of statistical techniques to a variety of problems or for those who are inte.
Covering important topics omitted from basic introductions to Stata, Microeconometrics Using Statashows how to do microeconometric research using Stata. It provides the most complete and up-to-date survey of microeconometric methods available in Stata. After a brief introduction to Stata, the authors present linear regression, simulation, and generalized least squares methods. The section on cross-sectional techniques is complete with up-to-date treatments of instrumental-variables methods for linear models as well as quantile regression methods. The next section covers estimators for the parameters of linear panel-data models. The book explores standard random-effects and fixed-effects methods, along with mixed linear models used in many areas outside of econometrics. After introducing methods for nonlinear regression models, the authors discuss how to code new, nonlinear estimators in Stata. They show how to easily implement new nonlinear estimators. The authors also cover inference using analytical and bootstrap approximations to the distribution of test statistics. The book then contains a section on methods for different nonlinear models, including multinomial, selection, count-data, and nonlinear panel-data models. By combining intuitive introductions and detailed discussions of Stata examples, this bookprovides an invaluable hands-on introduction to microeconometrics.
With Philip Pollock's Third Edition of A Stata Companion to Political Analysis, students quickly learn Stata via step-by-step instruction, more than 50 exercises, customized datasets, annotated screen shots, boxes that highlight Stata's special capabilities, and guidance on using Stata to read raw data. This attractive and value-priced workbook, an ideal complement to Pollock’s Essentials of Political Analysis, is a must-have for any political science student working with Stata.
An outstanding introduction to microeconometrics and how to do microeconometric research using Stata, this book covers topics often left out of microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. They begin by introducing simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book. They address each topic with an in-depth Stata example and demonstrate how to use Stata'真s programming features to implement methods for which Stata does not have a specific command.Multi/Card Deck Copy