Students experience data collection, analysis and inquiry in this LEGO® MINDSTORMS® NXT -based activity. They measure the position of an oscillating platform using a ultrasonic sensor and perform statistical analysis to determine the mean, mode, median, percent difference and percent error for the collected data.
Students learn about the statistical analysis of measurements and error propagation, reviewing concepts of precision, accuracy and error types. This is done through calculations related to the concept of density. Students work in teams to each measure the dimensions and mass of five identical cubes, compile the measurements into small data sets, calculate statistics including the mean and standard deviation of these measurements, and use the mean values of the measurements to calculate density of the cubes. Then they use this calculated density to determine the mass of a new object made of the same material. This is done by measuring the appropriate dimensions of the new object, calculating its volume, and then calculating its mass using the density value. Next, the mass of the new object is measured by each student group and the standard deviation of the measurements is calculated. Finally, students determine the accuracy of the calculated mass by comparing it to the measured mass, determining whether the difference in the measurements is more or less than the standard deviation.
The new breed of high-tech self-monitors (measuring heartrate, sleep, steps per day) might seem targeted at competitive athletes. But Talithia Williams, a statistician, makes a compelling case that all of us should be measuring and recording simple data about our bodies every day — because our own data can reveal much more than even our doctors may know.
Vision is the primary sense of many animals and much is known about how vision is processed in the mammalian nervous system. One distinct property of the primary visual cortex is a highly organized pattern of sensitivity to location and orientation of objects in the visual field. But how did we learn this? An important tool is the ability to design experiments to map out the structure and response of a system such as vision. In this activity, students learn about the visual system and then conduct a model experiment to map the visual field response of a Panoptes robot. (In Greek mythology, Argus Panoptes was the "all-seeing" watchman giant with 100 eyes.) A simple activity modification enables a true black box experiment, in which students do not directly observe how the visual system is configured, and must match the input to the output in order to reconstruct the unseen system inside the box.
Artist R. Luke DuBois makes unique portraits of presidents, cities, himself and even Britney Spears using data and personality. R. Luke DuBois weaves information from a multitude of sources into art and music exploring the tensions between algorithms, portraiture and temporal space. About the speakerR. Luke DuBois · Artist, composer, engineer R. Luke DuBois weaves information from a multitude of sources into art and music exploring the tensions between algorithms, portraiture and temporal space. In this talk, he shares nine projects — from maps of the country built using information taken from millions of dating profiles to a gun that fires a blank every time a shooting is reported in New Orleans. His point: the way we use technology reflects on us and our culture, and we reduce others to data points at our own peril.
Student teams assign importance factors, called "desirability points," the rock properties found in the previous lesson/activity in order to mathematically determine the overall best rocks for building caverns within. They learn the real-world connections and relationships between the rock and the important engineering properties for designing and building caverns (or tunnels, mines, building foundations, etc.).
Students become familiar with the online Renewable Energy Living Lab interface and access its real-world solar energy data to evaluate the potential for solar generation in various U.S. locations. They become familiar with where the most common sources of renewable energy are distributed across the U.S. Through this activity, students and teachers gain familiarity with the living lab's GIS graphic interface and query functions, and are exposed to the available data in renewable energy databases, learning how to query to find specific information for specific purposes. The activity is intended as a "training" activity prior to conducting activities such as The Bright Idea activity, which includes a definitive and extensive end product (a feasibility plan) for students to create.
Students use real-world data to evaluate the feasibility of solar energy and other renewable energy sources in different U.S. locations. Working in small groups, students act as engineers evaluating the suitability of installing solar panels at four company locations. They access data from the online Renewable Energy Living Lab from which they make calculations and analyze how successful solar energy generation would be, as well as the potential for other power sources at those locations. Then they summarize their results, analysis and recommendations in the form of feasibility plans prepared for a CEO.
***LOGIN REQUIRED*** Students will create an inquiry based mini lab given materials in the area of plant science. Students will work together to design protocols, collect data, and analyze results. Lesson 2 out of 4
The goals of this textbook are to help students acquire the technical skills of using software and managing a database, and develop research skills of collecting data, analyzing information and presenting results. We emphasize that the need to investigate the potential and practicality of GIS technologies in a typical planning setting and evaluate its possible applications. GIS may not be necessary (or useful) for every planning application, and we anticipate these readings to provide the necessary foundation for discerning its appropriate use. Therefore, this textbook attempts to facilitate spatial thinking focusing more on open-ended planning questions, which require judgment and exploration, while developing the analytical capacity for understanding a variety of local and regional planning challenges.
While this textbook provides the background for understanding the concepts in GIS as applicable to urban and regional planning, it is best when accompanied by a hands-on tutorial, which will enable readers to develop an in-depth understanding of the specific planning applications of GIS. Chapters in this text book are either composed by the editors using Creative Common materials, or linked to a book chapter scanned copy in the library reserve. In the end of each chapter, we also provided several discussion questions, together with contextual applications through some web links.
This course introduces the basic concepts and methods of statistics with applications in the experimental biological sciences. Demonstrates methods of exploring, organizing, and presenting data, and introduces the fundamentals of probability. Presents the foundations of statistical inference, including the concepts of parameters and estimates and the use of the likelihood function, confidence intervals, and hypothesis tests. Topics include experimental design, linear regression, the analysis of two-way tables, sample size and power calculations, and a selection of the following: permutation tests, the bootstrap, survival analysis, longitudinal data analysis, nonlinear regression, and logistic regression. Introduces and employs the freely-available statistical software, R, to explore and analyze data.
n this video, I show tips for making fake data. Fake data are useful for testing your understanding of certain statistical concepts, but are not actually that easy to make. The fake data made in this video will be used in subsequent videos to demonstrate
how to do statistics in Excel. - Created by a WyzAnt Tutor. Visit the tutor here: http://www.wyzant.com
This document provides synopses of frequently used time series of global-change data. Records are presented in multipage formats, each dealing with a specific site, region, or emissions species. The data records include tables, graphs, discussions of methods for collecting, measuring, and reporting the data, trends in the data, and references to literature providing further information. Instructions for citing specific data in Trends Online are provided for each compiled data set. Save
Prepared with pre-algebra or algebra 1 classes in mind, this module leads students through the process of graphing data and finding a line of best fit while exploring the characteristics of linear equations in algebraic and graphic formats. Then, these topics are connected to real-world experiences in which people use linear functions. During the module, students use these scientific concepts to solve the following hypothetical challenge: You are a new researcher in a lab, and your boss has just given you your first task to analyze a set of data. It being your first assignment, you ask an undergraduate student working in your lab to help you figure it out. She responds that you must determine what the data represents and then find an equation that models the data. You believe that you will be able to determine what the data represents on your own, but you ask for further help modeling the data. In response, she says she is not completely sure how to do it, but gives a list of equations that may fit the data. This module is built around the legacy cycle, a format that incorporates educational research feindings on how people best learn.
Does a set of data make you feel more comfortable? More successful? Then your interpretation of it is likely wrong. In a surprisingly moving talk, Susan Etlinger explains why, as we receive more and more data, we need to deepen our critical thinking skills. Because it's hard to move beyond counting things to really understanding them.
By 2020, there will be 50 billion devices connected to the Internet. Jonathan Strickland takes us on a tour through a living room of the future to see how this "Internet of Things" (IOT) will impact our daily lives.
حان الوقت للاستثمار في التدريب المباشر الذي يمكّن الموظفين من إجراء محادثات صعبة، كما تقول تاميكيا ميزلادي سميت في حديث ذكي مثير. تشارك سميث برنامج تدريب في مكان العمل يسمى "I’m G.R.A.C.E.D" والذي من شأنه أن يلهم الرؤساء والموظفين على حد سواء للتواصل بحيث يتم ذلك بالتعاطف والاحترام. خلاصة القول: دع الناس يعرفون دائمًا سبب أهمية عملهم.