The concept of statistical significance is explained, with specific numerical illustrations. (MNS)

The necessity for inferring and predicting in everyday life is discussed. Eight activities, ranging from sixth- to twelfth-grade levels, are suggested. (MK)

A survey of Pennsylvania secondary schools showed that relatively few (15 percent) schools offered probability and statistics regularly as a complete course and of those which did, the course was elected primarily by seniors. Reasons for the lack of offerings are analyzed. (DT)

A program is proposed for teaching statistics and probability to elementary school children. Task analysis is used to determine concept sequence and detailed behavioral objectives are specified. (CR)

A variety of suggestions for making the mathematics curriculum more meaningful and interesting to students are described. Activities that incorporate real-world situations are provided for verbal items, common and decimal fractions, estimations and rounding off numbers, large and small numbers, geometry, probability, and statistics. (KR)

Discusses an experiment for elementary students based on the principle that the faster an object is moving when it is dropped, the greater the distance it will travel away from the drop point. Also discusses concepts of probability and statistics in the experiment and methods of alternative assessment. (Author/MKR)

Described is a strategy that allows students to experiment with probability without applying formulas to solve problems. Students are able to intuitively develop concepts of probability before formal definitions and properties. Sample problems are included along with BASIC programs for some of the problems. (KR)

Illustrates some applications of elementary probability and statistics to epidemiology, the branch of medical science that attempts to discover associations between events, patterns, and the cause of disease in human populations. Uses real-life examples involving cancer's link to smoking and the AIDS virus. (MDH)

Proposes an alternative means of approximating the value of complex integrals, the Monte Carlo procedure. Incorporating a discrete approach and probability, an approximation is obtained from the ratio of computer-generated points falling under the curve to the number of points generated in a predetermined rectangle. (MDH)