ERIC Number: ED578967
Record Type: Non-Journal
Publication Date: 2011-Dec-16
Pages: 512
Abstractor: As Provided
ISBN: 978-0-8261-0720-6
ISSN: N/A
EISSN: N/A
Available Date: N/A
Statistics and Data Interpretation for Social Work
Rosenthal, James A.
Springer
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to provide a solid foundation in statistics. It also addresses tools used by researchers to describe and summarize data ranging from single variables to assessing the relationship between variables and cause and effect among variables. The second section focuses on inferential statistics, describing how researchers draw conclusions about whole populations based on data from samples. This section also covers confidence intervals and a variety of significance tests for examining relationships between different types of variables. Additionally, tools for multivariate analyses and data interpretation are presented. Key features include: (1) Addresses the role of statistics in evidence-based practice and program evaluation; (2) Features examples of qualitative and quantitative analysis; (3) Each chapter contains exercise problems and questions to enhance student learning; (4) Includes electronic data sets taken from actual social work arenas; and (5) Offers a full ancillary digital packet including a student guide to SPSS with accompanying Data Set, an Instructor's Manual, PowerPoint slides, and a Test Bank.
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research, Research Methodology, Mathematical Concepts, Statistical Inference, Intervals, Multivariate Analysis, Statistical Data, Evidence Based Practice, Program Evaluation, Qualitative Research, Statistical Distributions, Statistical Analysis, Measurement, Scores, Correlation, Sample Size, Risk, Regression (Statistics), Research Design, Causal Models, Mathematical Formulas, Statistical Significance, Hypothesis Testing, Error of Measurement, Computation, Nonparametric Statistics, Generalizability Theory
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Publication Type: Books; Guides - Non-Classroom
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
IES Cited: ED577092
Author Affiliations: N/A