Economic Update: Building Worker Coops
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Data Analysis
The applet in this section allows for simple data analysis of univariate data. Users can either generate normal or uniform data for k samples or copy and paste data from another source to a text box. A univariate analysis is performed for all k samples.
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The Central Limit Theorem
The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform).
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Star Library: Histogram Sorting
This activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), that not all histograms are easy to classify, that there is a difference between models (normal, uniform) and characte
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Fostering Simulation-based Learning in Medical Education with Collaboration Script
Active participation of learners is considered a major benefit of simulation-based learning. However, in most courses only few persons can act simultaneously in the simulator while the remaining group observes the running scenario. We investigated how these observation phases can be instructionally designed for more active participation. Research in educational psychology suggests the use of collaboration scripts to structure these observation phases. A collaboration script is an instruction tha
Author(s): Zottmann Jan,Dieckmann Peter,Rall Marcus,Fischer F

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Adaptive FIR Filtering
In this laboratory, students implement a real-time adaptive FIR filter, investigate the convergence of the least mean squares (LMS) algorithm, and apply the adaptive filter to the problems of system identification and echo cancellation.
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Uniform convergence and pointwise convergence
The aim of this material is to introduce the student to two notions of convergence for sequences of real-valued functions. The notion of pointwise convergence is relatively straightforward, but the notion of uniform convergence is more subtle. Uniform convergence is explained in terms of closed function balls and the new notion of sets absorbing sequences. The differences between the two types of convergence are illustrated with several examples. Some standard facts are also discussed: a uniform
Author(s): Feinstein Joel F. Dr

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Basketball team, Pomona College
The members of the 1903 Pomona College women's basketball team pose for a photograph outside of Holmes Hall wearing their uniforms. One student is holding a basketball with "'03" written on it.
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Football player, Pomona College Prep
Pomona College Prep student Charles Moorman poses for a photograph in his football uniform on the athletic field.
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Football player, Pomona College
Pomona College student Laurence Voorhees poses for a photograph wearing his football uniform in front of a house.
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Football player, Pomona College
Pomona College student William Wharton poses for a photograph inside Renwick Gymnasium wearing his football uniform.
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Pomona College sophomore men, class of 1905
Sophomore men of the class of 1905 pose for a photograph outside in two rows. All of the students are wearing matching sweaters with "1905" across the breast. Vernon Wolcott is on the first row, first on the right. Wallace Robb is on the second row, first on the right.
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Track and field athlete, Pomona College
Pomona College student Laurence Voorhees poses for a photograph wearing his track and field uniform in front of a house.
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Football player, Pomona College
George S. Hinckley (class of 1903) sits on a touchdown ball next to Renwick Gymnasium while the umpire considers a disputed play.
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Sumner dining room group, Pomona College
A group of Pomona College students pose for a photograph in the dining room of Sumner Hall. The men are standing in the back row, the women are seated in front.
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Behavior of steel members with trapezoidally corrugated webs and tubular flanges under static loadin
Engineers have long realized that corrugated webs enormously increase steel girdersâ stability against buckling and can result in very economical design. Recently, the new idea of combining the tubular flanges with corrugated webs brought new issues of research. The objective of the research presented in this thesis is to investigate the behavior of steel members with corrugated webs and tubular flanges subjected to shear, bending, and axial compression. Relative buckling modes are also disco
Author(s): Wang, Xiaobo

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Distance Formula
This video explains how to derive the distance formula, which is used to find the straight distance between two points in a coordinate plane, by Using what we know about the Pythagorean theorem. The distance formula is a standard formula that allows us to plug a set of coordinates into the formula and easily calculate the distance between the two. (4:26)
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Instalaciones I. Grado en Arquitectura
La asignatura Instalaciones I tiene como objetivo general que el alumno adquiera los conocimientos fundamentales de las instalaciones presentes en la edificación mediante el aprendizaje de los conceptos básicos, la terminología, la teoría y la metodología necesarias para que el alumno sea capaz de entender, plantear, diseñar y ubicar las instalaciones en cualquier edificación.
Author(s): Gemma Vazquez Arenas

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Voter Experiment
This resource consists of a Java applet and expository text. The applet is a simulation of the voter experiment, an interacting partile system that consists of a rectangular array of sites. At each discrete time unit, a site is chosen at random, a neighboring site is chosen, and the color of the first site is changed to that of the neighbor. The applet illustrates clustering of the colors and convergence to consensus.
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Bivariate Uniform Experiment
This resource consists of a Java applet and expository text. The Java applet illustrates the bivariate uniform distribution on three types of regions: a square, a circle, and a triangle. Simulated points from the distribution are shown as dots in a scatterplot.
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