R. Zia and B. Schmittmann, Am. J. Phys., 71 (9), 859-875 (2003).
The most frequently studied quantities of a statistical variable are its average and standard deviation. Yet, its full distribution often carries very interesting information and can…
N. Mermin, Am. J. Phys., 52 (4), 362-365 (1983).
Stirling’s approximation to n! and other estimates are developed using elementary arguments. The aim is to shed light on why these approximations work so well. An elementary and…
D. Landau, S. Tsai, and M. Exler, Am. J. Phys., 72 (10), 1294-1302 (2004).
The authors describe a Monte Carlo algorithm for sampling the density of states directly by doing a random walk in energy space. The probability of a microstate is computed at any…
J. Tobochnik, H. Gould, and J. Machta, Am. J. Phys., 73 (8), 708-716 (2004).
Several Monte Carlo algorithms and applications that are useful for understanding the concepts of temperature and chemical potential are discussed. The authors then introduce a…