Articles by "Stata"

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Lisa Daniels, Nicholas W. Minot ... 392 pages - ISBN-10: 1506371833 - ISBN-13: 978-1506371832 ... Publisher : SAGE Publications; (January, 2019) - Language: English.


An Introduction to Statistics and Data Analysis Using Stata by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

Alan C. Acock ... 500 pages - ISBN-10: 1597181420 - ISBN-13: 978-1597181426 ... Publisher: Stata Press; 4th Edition (April, 2014) - Language: English.


A Gentle Introduction to Stata, Fourth Edition is for people who need to learn Stata but who may not have a strong background in statistics or prior experience with statistical software packages. After working through this book, you will be able to enter, build, and manage a dataset, and perform fundamental statistical analyses. This book is organized like the unfolding of a research project. You begin by learning how to enter and manage data and how to do basic descriptive statistics and graphical analysis. Then you learn how to perform standard statistical procedures from t tests, nonparametric tests, and measures of association through ANOVA, multiple regression, and logistic regression. Readers who have experience with another statistical package may benefit more by reading chapters selectively and referring to this book as needed. The fourth edition has incorporated numerous changes that were new with Stata 13. Coverage of the marginsplot command has expanded. This simplifies the construction of compelling graphs. There is a new chapter showing how to estimate path models using the sem (structural equation modeling) command. Menus have been updated, and several minor changes and corrections have been included based on suggestions from readers.

Nancy Whittier, Tina Wildhagen, Howard J. Gold ... 696 pages - Publisher: Rowman & Littlefield Publishers (January, 2019) ... Language: English - ISBN-10: 1538109832 - ISBN-13: 978-1538109830.

Statistics for Social Understanding: With Stata and SPSS introduces students to the way statistics is used in the social sciences--as a tool for advancing understanding of the social world. Written in an engaging and clear voice and based on the latest research on the teaching and learning of quantitative material, the text is geared to introductory students in the social sciences, including those with little quantitative background. It covers the conceptual aspects of statistics even when the mathematical details are minimized. Informed by research on teaching and learning in statistics, the book takes a universal design approach to accommodate diverse learning styles. With an early chapter on cross-tabulation, a focus on comparisons between groups throughout, and a unique chapter on causality, the text shows students the power of statistics for answering important real-world questions.

By providing thorough coverage of social science statistical topics, a balanced approach to calculation, and step-by-step directions on how to use statistical software, authors Nancy Whittier, Tina Wildhagen, and Howard J. Gold give students the ability to analyze data and explore and answer exciting questions. To accommodate changing undergraduate courses, the text incorporates examples from both Stata and SPSS in every chapter and provides practice problems of every type as well as readily available datasets for classroom use, including the General Social Survey, American National Election Study, and more. Each chapter concludes with a chapter summary, a section on using Stata, a section on using SPSS, and practice problems.

Prasad Kothari ... 176 pages - Publisher: Packt Publishing; (October, 2015) ... Language: English - AmazonSIN: B013R02BOC.

STATA is an integrated software package that provides you with everything you need for data analysis, data management, and graphics. STATA also provides you with a platform to efficiently perform simulation, regression analysis (linear and multiple) [and custom programming. This book covers data management, graphs visualization, and programming in STATA. Starting with an introduction to STATA and data analytics you'll move on to STATA programming and data management. Next, the book takes you through data visualization and all the important statistical tests in STATA. Linear and logistic regression in STATA is also covered. As you progress through the book, you will explore a few analyses, including the survey analysis, time series analysis, and survival analysis in STATA. You'll also discover different types of statistical modelling techniques and learn how to implement these techniques in STATA.

Thomas Cleff ... 497 pages - Publisher: Springer; (July, 2019) ... Language: English - AmazonSIN: B07V82V6L6.

This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.

Ulrich Kohler, Frauke Kreuter ... 497 pages - Publisher: Stata Press; 3rd edition (August, 2012) ... Language: English - ISBN-10: 1597181102 - ISBN-13: 978-1597181105.

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks. The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand. Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

StataCorp Stata MP v16.0 [Size: 337 MB] ... StataCorp Stata MP 16 for Windows PC also known as Stata/MP provides the most extensive multicore support of any statistics and data management package. Stata/MP is the fastest and largest version of Stata. Almost every computer can take advantage of the advanced multiprocessing capabilities of Stata/MP. Stata/MP lets you analyze data in one-half to two-thirds the time compared with Stata/SE on inexpensive dual-core laptops and in one-quarter to one-half the time on quad-core desktops and laptops. Stata/MP runs even faster on multiprocessor servers. Stata/MP supports up to 64 cores/processors. Stata/SE can analyze up to 2 billion observations. Stata/MP can analyze 10 to 20 billion observations on the largest computers currently available and is ready to analyze up to 1 trillion observations once computer hardware catches up. Stata/MP also allows 120000 variables compared to 32767 variables allowed by Stata/SE. Some procedures are not parallelized and some are inherently sequential, meaning they run the same speed in Stata/MP. For a complete assessment of Stata/MP’s performance, including command-by-command statistics. Stata/MP is the multiprocessor and multicore version of Stata. It’s primary purpose is to run faster. Most of the new features in Stata have been parallelized to run faster on Stata/MP, sometimes much faster.

Stata Software for Statistics and Data Science v15 [Size: 295.5 MB] ... Stata is a general-purpose statistical software package created in 1985 by StataCorp. Most of its users work in research, especially in the fields of economics, sociology, political science, biomedicine and epidemiology.[citation needed]Stata's capabilities include data management, statistical analysis, graphics, simulations, regression analysis (linear and multiple), and custom programming. The name Stata is a portmanteau of the words statistics and data. The correct English pronunciation of Stata "must remain a mystery"; any of "Stay-ta", "Sta-ta" or "Stah-ta" are considered acceptable.

Features: Linear models: regression • censored outcomes • endogenous regressors • bootstrap, jackknife, and robust and cluster–robust variance • instrumental variables • three-stage least squares • constraints • quantile regression • GLS • more. Panel/longitudinal data: random and fixed effects with robust standard errors • linear mixed models • random-effects probit • GEE • random- and fixed-effects Poisson • dynamic panel-data models • instrumental variables • panel unit-root tests • more. Multilevel mixed-effects models: continuous, binary, count, and survival outcomes • two-, three-, and higher-level models • generalized linear models • nonlinear models • random intercepts • random slopes • crossed random effects • BLUPs of effects and fitted values • hierarchical models • residual error structures • DDF adjustments • support for survey data • more. Binary, count, and limited outcomes: logistic, probit, tobit • Poisson and negative binomial • conditional, multinomial, nested, ordered, rank-ordered, and stereotype logistic • multinomial probit • zero-inflated and left-truncated count models • selection models • marginal effects • more. Extended regression models (ERMs): combine endogenous covariates, sample selection, and nonrandom treatment in models for continuous, interval-censored, binary, and ordinal outcomes • more.

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