Literature Index

Flipped classrooms have become an interesting alternative to traditional lecture-based courses throughout the undergraduate curriculum. In this article, we compare a flipped classroom approach to the traditional lecture-based approach to teaching introductory biostatistics to first-year graduate students in public health. The traditional course was redesigned to include video lectures and online quizzes which the students were expected to complete before coming to class, followed by a short in-class lecture and time working on applied statistics problems in class. We compared the opinions of the biostatistics field and confidence applying biostatistics methods of 46 students who took the flipped course to 52 students who took the traditional, lectured-based course offering. We found similar end-of-semester opinions and levels of confidence between students in the flipped classes and those in the traditional, lecture-focused classes, though students in the flipped course reported very high satisfaction with the model.

Florence Nightingale is remembered as a pioneer of nursing and a reformer of hospitals. She herself saw her mission in larger terms: to serve humanity through the prevention of needless illness and death. For much of her long life (1820-1910) she pursued this mission with a fierce determination that gave everything she did a singular coherence. Her greatest contributions were undoubtedly her efforts to reform the British military health-care system and her establishment, through the founding of training programs and the definitions of sound professional standards, of nursing as a respected profession. Much of what now seems basic in modern health case can be traced to the 19th century. Less well known, because it has been neglected by her biogrpahers, is her equally pioneering use of the new advanced techniques of statistical analysis in those battles.

A course in time series analysis offers a number of unique opportunities for introducing mathematically oriented students to the applications of statistics. Characteristics of such a course and its suitability as a "first course" in statistics are discussed.

In college courses that use group work to aid learning and evaluation, class groups are often selected randomly or by allowing students to organize groups themselves. This article describes how to control some aspect of the group structure, such as increasing schedule compatibility within groups, by forming the groups using multidimensional scaling. Applying this method in an undergraduate statistics course has resulted in groups that have been more homogeneous with respect to student schedules than groups selected randomly. For example, correlations between student schedules increased from a mean of 0.29 before grouping to a within-group mean of 0.50. Further, the exercise motivates class discussion of a number of statistical concepts, including surveys, association measures, multidimensional scaling, and statistical graphics.