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Data Management & Organization

  • This is a chapter on data wrangling excerpted from a book on data science. The book is “Modern Data Science with R,” and the authors are Benjamin J. Baumer, Daniel T. Kaplan, and Nicholas J. Horton. It contains the R code needed to do basic things with data such as sorting, arranging, and summarizing data.

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  • This site is a lesson on using SQL. It starts with a simple SELECT query. The user must type in the correct command to select certain columns from a database. Once the user has completed the first lesson, then he or she may continue to more complicated lessons.

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  • Big data analysis is explained in this online course that introduces the user to the tools Hadoop and Mapreduce. These tools allow for the parallel computing necessary to analyze large amounts of data.

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  • This is a web application framework for R, in which you can write and publish web apps without knowing HTML, Java, etc. You create two .R files: one that controls the user interface, and one that controls what the app does. The site contains examples of Shiny apps, a tutorial on how to get started, and information on how to have your apps hosted, if you don't have a server.

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  • This software allows you to extract data from published graphs. There is a web-based app and a downloadable version. First, you provide the software with a picture of the graph in question. Then you give it two points on the x-axis and two points on the y-axis for reference. Then you click on the points on the graph that you want to extract. The points are put into a .csv file.

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  • This complete lesson plan, which includes assessments, is based upon a data set partially discussed in the article "Female Hurricanes are Deadlier than Male Hurricanes." The data set contains archival data on actual fatalities caused by hurricanes in the United States between 1950 and 2012. Students analyze and explore this hurricane data in order to formulate a question, design and implement a plan to collect data, analyze the data by measures and graphs, and interpret the results in the context of the original question.
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  • A reference for analyzing large, complex data sets. Helpful for various levels of students.

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  • DataFerrett is a unique data analysis and extraction tool -- with recoding capabilities -- to customize federal, state, and local data to suit your requirements. Using DataFerrett, you can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands. The DataFerrett helps you locate and retrieve the data you need across the Internet to your desktop or system, regardless of where the data resides. You can then develop and customize tables. Selecting your results in your table you can create a chart or graph for a visual presentation into an html page. Save your data in the databasket and save your table for continued reuse. The DataFerrett is a Beta testing version that will incorporate the latest bug fixes, enhancements, and new functionality that will be rolled into the DataFerrett after testing has been completed.

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  • Beware of bugs in the above code; I have only proved it correct, not tried it. is a quote from American computer scientist Donald E. Knuth (1938 - ). The quote was written on March 22, 1977 as the last sentence of a five-page memo entitled "Notes on the van Emde Boas construction of priority deques: An instructive use of recursion."
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  • A sketch by Anastasia Mandel reinterpreting Cattle by a Lake by Sidney Richard Percy (1862) with the statistical caption "A multimodal distribution with small outliers." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.

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