Social Science Data File Directory
Author :
Publisher :
Page : 394 pages
File Size : 35,30 MB
Release : 1975
Category : Bibliographical services
ISBN :
Author :
Publisher :
Page : 394 pages
File Size : 35,30 MB
Release : 1975
Category : Bibliographical services
ISBN :
Author : Vivian S. Sessions
Publisher :
Page : 330 pages
File Size : 29,34 MB
Release : 1974
Category : Information storage and retrieval systems
ISBN :
International listing of computer data bases and their data components. Alphabetical arrangement by institutions or agencies. Entries include address, telephone number, persons in charge, subject, details about the computer, storage media, output media, data products, and access information. Indexes by subject, institution, personnel, and geographical location.
Author : National Referral Center (U.S.)
Publisher :
Page : 234 pages
File Size : 33,1 MB
Release : 1965
Category : Information services
ISBN :
Author :
Publisher :
Page : pages
File Size : 25,7 MB
Release : 1967
Category : Social sciences
ISBN :
Author :
Publisher :
Page : 520 pages
File Size : 27,51 MB
Release : 1975
Category : United States
ISBN :
Author :
Publisher :
Page : 752 pages
File Size : 48,90 MB
Release : 1988
Category : Data centers
ISBN :
Author : Brian J. Fogarty
Publisher : SAGE Publications Limited
Page : 566 pages
File Size : 10,47 MB
Release : 2023-03-11
Category : Social Science
ISBN : 1529614228
Relevant, engaging, and packed with student-focused learning features, this book provides the basic step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and the language and functionality of R and R Studio software, it uses examples from across the social sciences to show students how to apply abstract statistical and methodological principles to their own work. Maintaining a student-friendly pace, it goes beyond a normal introductory statistics book and shows students where data originates and how to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives students not only the tools they need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what they have learned.
Author : Kathleen Thacker
Publisher :
Page : 696 pages
File Size : 26,88 MB
Release : 1989
Category : Language Arts & Disciplines
ISBN : 9780934213189
Author : David J. Makowski
Publisher :
Page : 212 pages
File Size : 48,76 MB
Release : 1980
Category : Continuing education
ISBN :
Author : Quan Li
Publisher : Oxford University Press
Page : 369 pages
File Size : 40,88 MB
Release : 2018
Category : Computers
ISBN : 0190656212
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 in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.