A recent article in "The Physics Teacher" describes a method for analyzing a systematic error in a Boyle's law laboratory activity. Systematic errors are important to consider in physics labs because they tend to bias the results of measurements. There are numerous laboratory examples and resources that discuss this common source of error.

We develop an Easy Java Simulation (EJS) model for students to experience the physics of idealized one-dimensional collision carts. The physics model is described and simulated by both continuous dynamics and discrete transition during collision. In designing the simulations, we discuss briefly three pedagogical considerations namely (1) a…

This activity makes students a part of an investigation that determines the frequency of a particular plant variety in a simulated population. Provides an opportunity for students to observe the inherent variability of estimates, observe the relationship between sample size and sampling error, and consider aspects of research design. (Author/SAH)

Discusses the problems associated with teaching uncertainties in measurements and significant figures. Appendices present an experiment on measurement that introduces uncertainty in measurement, and an exercise in significant figures. (CS)

Argues against a rule-based, algorithmic approach to measurement in introductory chemistry courses. Describes a learning activity that leads students to understand the need for rules and the application of those rules in measurement. (DDR)

Discusses the use of linear regression methods to extrapolate experimental data. Describes the method of averages and two weighted least squares. Calculates the error range of each method. (YP)

Outlines the simple exercise of measuring the length of an object as a concrete paradigm of the entire process of making chemical measurements and treating the resulting data. Discusses the procedure, significant figures, measurement error, spurious data, rejection of results, precision and accuracy, and student responses. (TW)

Describes two simple methods of error analysis: (1) combining errors in the measured quantities; and (2) calculating the error or uncertainty in the slope of a straight-line graph. Discusses significance of the error in the comparison of experimental results with some known value. (MDH)