Although stanine scores are used by many schools for posting students' test results in permanent records, not all teachers are confident in their interpretation of what stanine scores signify. This quiz and accompanying correct answers and explanations are offered to help make these scores more useful to practitioners. (LC)

The first of a series of quizzes on types of derived scores concerns interpreting grade-equivalent (GE) scores. The true-false items require a response about whether the stated interpretation of the GE score is sound. An answer key explains specific scoring methods. (CM)

Normal Curve Equivalents (NCEs), a new score system for standardized tests, are used by school districts in reporting results to federal funding agencies. The author uses a quiz format to answer questions on the use of NCE scores. (EGS)

A true-false measure concerning the interpretation of intelligence quotients (IQ) is presented. The correct responses to the 10 items, and a brief explanation of each, are also included. The author attempts to reveal many misconceptions about the interpretation of IQ scores. (DWH)

This quiz and its explanations are designed to help teachers and counselors assist students in deciding the meaning of their scores on the Scholastic Aptitude Test and the American College Test. (BW)

Percentile scores appear to be the easiest standardized test scores for parents to understand. Yet in this true-false test, Hills reveals commonly held misconceptions about percentile score reports. (LC)

A quiz is presented that may call the attention of school personnel to regression effects in educational measurement, and clarify the meaning of statistical regression for educators in schools. Ten questions and their answers explore regression in the contexts of classroom testing, grading, and performance assessment. (SLD)

A scenario and accompanying questions and answers are posed to help educators examine possible problems in interpreting a student's test score profile. Profiles developed and used soundly are very helpful, but possible pitfalls in test interpretation must be recognized. (SLD)

Test bias detection methods based on item response theory (IRT) are reviewed. Five such methods are commonly used: (1) equality of item parameters; (2) area between item characteristic curves; (3) sums of squares; (4) pseudo-IRT; and (5) one-parameter-IRT. A table compares these and six newer or less tested methods. (SLD)