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Calver, Michael; Fletcher, Douglas – American Biology Teacher, 2020
Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on…
Descriptors: Statistical Analysis, Data Collection, Biology, Science Laboratories
Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension
Derryberry, DeWayne R.; Schou, Sue B.; Conover, W. J. – Journal of Statistics Education, 2010
Students learn to examine the distributional assumptions implicit in the usual t-tests and associated confidence intervals, but are rarely shown what to do when those assumptions are grossly violated. Three data sets are presented. Each data set involves a different distributional anomaly and each illustrates the use of a different nonparametric…
Descriptors: Nonparametric Statistics, Hypothesis Testing, Instruction, Statistical Distributions
Eudey, T. Lynn; Kerr, Joshua D.; Trumbo, Bruce E. – Journal of Statistics Education, 2010
Null distributions of permutation tests for two-sample, paired, and block designs are simulated using the R statistical programming language. For each design and type of data, permutation tests are compared with standard normal-theory and nonparametric tests. These examples (often using real data) provide for classroom discussion use of metrics…
Descriptors: Statistical Distributions, Hypothesis Testing, Relationship, Statistical Significance