Flame Emission Spectroscopy (FES) is a powerful analytical technique widely used for identifying and quantifying elements in various samples. In this laboratory experiment, undergraduate students were introduced to FES and its significance in analytical chemistry. The experiment aimed to provide students with hands-on experience in constructing…

The Poisson distribution describes the probability of a certain number of events occurring in an interval of time when the occurrence of the individual events is independent of one another and the events occur with a fixed mean rate. Probably the best-known example of the Poisson distribution in the physics curriculum is the temporal distribution…

In this work, we have developed an alternative device composed by an Arduino board and an INA219 sensor to experimentally obtain the mathematical formulas describing the charge and discharge of the capacitor for educational proposes. We have obtained excellent agreement between theoretical prediction and experimental measurements. The INA219 DC…

A simple mistake in properly setting up a measuring device caused millions of dollars to be spent in correcting the initial optical failure of the Hubble Space Telescope (HST). This short article is intended as a lesson for a physics laboratory and discussion of errors in measurement.

A low-cost and simple setup to measure the densities of liquids is introduced herein. The results and reliability of this setup were evaluated for pure liquids, water-ethanol binary mixtures, and aqueous NaCl solutions. The constructed densitometer provided density values with acceptable relative errors (less than ±3.0%), which were compared to…

Systematic errors can cause measurements to deviate from the actual value of the quantity being measured. Faulty equipment (such as a meterstick that is not marked correctly), inaccurate calibration of measuring devices (such as a scale to measure mass that has not been properly zeroed), and improper use of equipment by the experimenter (such as…

Systematic errors are often unavoidable in the introductory physics laboratory. As has been demonstrated in many papers in this journal, such errors can present a fundamental problem for data analysis, particularly when comparing the data to a given model. In this paper I give three examples in which my students use popular curve-fitting software…

The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…

We present a fun activity that can be used to introduce students to error analysis: the M&M game. Students are told to estimate the number of individual candies plus uncertainty in a bag of M&M's. The winner is the group whose estimate brackets the actual number with the smallest uncertainty. The exercise produces enthusiastic discussions and…

Testing the pH of various liquids is one of the most popular activities in 5th- through 8th-grade classrooms. The author presents an extensive pH-testing lesson based on a 5E (engagement, exploration, explanation, extension, and evaluation) teaching model. The activity provides students with the opportunity to learn about pH and how it relates to…

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)

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)

Describes a computerized method to test error analysis that helps motivate introductory physics students to learn the topic. The computer generates a test consisting of four topics from a list of 10 that students should know. Numerical data within realistic ranges are also generated. (JN)

Investigates minimizing errors in computational methods commonly used in chemistry. Provides a series of examples illustrating the propagation of errors, finite difference methods, and nonlinear regression analysis. Includes illustrations to explain these concepts. (MVL)

Contends that the nature of physics has been misrepresented by blurring or ignoring important distinctions between "errors" and "discrepancies" and that dealing with these and related problems can improve students' enjoyment of labs and understanding of physics. Nature of physics, role of experiments, experimental errors, and error analysis are…