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Sotoudeh, Ramina; DiMaggio, Paul – Sociological Methods & Research, 2023
Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…
Descriptors: Algorithms, Simulation, Prediction, Correlation
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals

Tyler, David E. – Multivariate Behavioral Research, 1982
Miller and Farr's algorithm for the index of redundancy is shown to be incorrect by means of a counterexample. The consequences of this error for other conclusions drawn by the authors are discussed. (Author/JKS)
Descriptors: Algorithms, Correlation, Data Analysis, Multivariate Analysis
Dickinson, Wendy B. – 2000
This study uses an algorithm-based visual display technique (FACES) to provide enhanced detection of multivariate outliers within large-scale data sets. The FACES computer graphing algorithm (H. Chernoff, 1973) constructs a cartoon-like face, using up to 18 variables for each case. A major advantage of FACES is the ability to store and show the…
Descriptors: Algorithms, Correlation, Grade 8, Graphs

Dreger, Ralph Mason; And Others – Multivariate Behavioral Research, 1988
Seven data sets (namely, clinical data on children) were subjected to clustering by seven algorithms--the B-coefficient, Linear Typal Analysis; elementary linkage analysis, Numerical Taxonomy System, Statistical Analysis System hierarchical clustering method, Taxonomy, and Bolz's Type Analysis. The little-known B-coefficient method compared…
Descriptors: Algorithms, Children, Clinical Diagnosis, Cluster Analysis
van der Burg, Eeke; de Leeuw, Jan – 1988
A non-linear version of redundancy analysis is introduced. The technique is called REDUNDALS. It is implemented within the computer program for canonical correlation analysis called CANALS. The REDUNDALS algorithm is of an alternating least square (ALS) type. The technique is defined as minimization of a squared distance between criterion…
Descriptors: Algorithms, Attitude Measures, Computer Oriented Programs, Correlation