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Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences
Strange, Marty; Johnson, Jerry; Showalter, Daniel; Klein, Robert – Rural School and Community Trust, 2012
"Why Rural Matters 2011-12" is the sixth in a series of biennial reports analyzing the contexts and conditions of rural education in each of the 50 states and calling attention to the need for policymakers to address rural education issues in their respective states. While it is the sixth in a series, this report is not simply an…
Descriptors: Rural Schools, Rural Education, Educational Policy, Annual Reports
Jones, Gail – 1989
A brief historical background of discriminant analysis is given, with a description of the variety of roles that discriminant analysis can perform. Focus is on the classification role of discriminant analysis and how it can be performed by using Fisher's classification functions or the canonical discriminant functions. A small hypothetical data…
Descriptors: Classification, Discriminant Analysis, Literature Reviews, Multivariate Analysis

Kelly, Ivan; Ryan, Alan – Science Teacher, 1983
Explains the use of contingency tables as a tool in assessing variables to determine whether a relationship exists. Develops an example hypothesis step-by-step, noting the scientific processes and attitudes being addressed. Cautions that a large difference, which suggests a relationship, is not explanation since correlation does not guarantee…
Descriptors: Classification, Data Analysis, Data Collection, High Schools