Credit Scoring, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook "Thank you and thank you again for providing a complete, well-structured, and easy-to-understand online resource. Every other website or snobbish research paper has not deigned to explain things in words consisting of less than four syllables. I was tossed to and fro like a man holding on to a frail plank that he calls his determination until I came across your electronic textbook...You have cleared the air for me. You have enlightened. You have illuminated. — Mr. "As a professional medical statistician of some 40 years standing, I can unreservedly recommend this textbook as a resource for self-education, teaching and on-the-fly illustration of specific statistical methodology in one-to-one statistical consulting. — Mr. "Excellent book. — Dr. "Just wanted to congratulate whoever wrote the 'Experimental Design' page. — James A. Read More Testimonials >> StatSoft has freely provided the Electronic Statistics Textbook as a public service since 1995. Proper citation:
How Much CO2 Is Created By… Every action, every event, every person, everything emits a certain amount of carbon. This interactive visualization examines some of those scenarios. Play around to learn some interesting and surprising information about how much carbon is released during various activities. About this data The data leveraged in this application is derived from a number of sources, including: “How Bad Are Bananas?”, Agence France-Presse, Carbon Trust Report, comScore Inc., Google, Guardian, Heathrow Airport Limited, JP Morgan, Real Climate, The Independent, The New York Times, Times, United States Environmental Protection Agency, and University of Oxford Environmental Change Institute. Share Downloads Download the Application Design Partner David McCandless
Data Preprocessing Tools Advance Macintosh Data Recovery Software and macintosh file retrieval tool for deleted or formatted apple macintosh hard drives. Mac Recovery Software is the most advanced Mac File Recovery application that recovers data from formatted, deleted or corrupted Mac partitions or External mac hard drives. Best Mac Data Recovery Tools is risk-free mac data recovery utility that recovers all important data lost accidental format, virus, file/directory deletion, or even a sabotage. Software fixes damaged mac hard disk and restore mac files within minutes. Platform: Windows Publisher: macdatarecovery.net Date: Size: 1730 KB ADRC Data Recovery Tools v1.0 contains a collection of DIY data recovery tools that supports a wide variety of drives (fixed drives or removable drives) and file systems (FAT12, FAT16, FAT32 and NTFS) for Windows 95/ 98, Windows ME, Windows NT, Windows 2000, Windows XP and Windows 2003 server.The software incorporates extremely simple GUI with novice users in mind.
Regression, ANOVA, and general statistics software for Macintosh computers (Macs) (Updated July 2014 with Salstat). Also see: G*Power Configurations Available: Older versions: 680x0; 680x0+FPU; PowerPC native; OS X (Universal Binary); Windows and DOS Current Version: 3.17 / requires OS 10.6 or newer Listing updated: 7/2013 (program updated 2013) G*Power was developed by Axel Buchner to provide power analyses for the most common statistical tests in behavioral research: t-tests, F-tests (including ANOVA, regression, etc.), and Chi-squared tests. gretl gretl can do some general statistical routines and many specialized ones; it is in our “special purpose and general math programs” page. GMT - The Generic Mapping Tools Configurations: UNIX, OS X; since you compile it, Universal Current version: 4.59 Program updated: 1-1-13 Listing updated: 7-7-13 A collection of command-line tools that run on all Unix-like systems, including Mac OS X. Graphviz Configurations: PPC (older versions), 10.5+ (current) Current Version: 2.20.3 Listing updated: 7-7-13 gnuplot MacAnova Matplotlib OpenEpi
Weka 3 - Data Mining with Open Source Machine Learning Software in Java Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Weka supports deep learning!
Unit Operations in Food Processing - R. L. Earle This is the free web edition of a popular textbook known for its simple approach to the diversity and complexity of food processing. First published in 1966 but still relevant today, Unit Operations in Food Processing explains the principles of operations and illustrates them by individual processes. Each Chapter contains unworked examples to help the student food technologist or process engineer gain a grasp of the subject. Now in electronic form, fully searchable and cross-linked, this online resource will also be a useful quick reference for technical workers in the food industry. The author, Dick Earle (owner of the copyright) gives permission to download and print any part or all of the text for any nonprofit purposes. Content can be printed by individual page, or as complete Chapters. Funding, publication and hosting for the book is provided by the New Zealand Institute of Food Science & Technology (NZIFST).
Do Faster Data Manipulation using These 7 R Packages Introduction Data Manipulation is an inevitable phase of predictive modeling. A robust predictive model can’t be just be built using machine learning algorithms. But, with an approach to understand the business problem, the underlying data, performing required data manipulations and then extracting business insights. Among these several phases of model building, most of the time is usually spent in understanding underlying data and performing required manipulations. What is Data Manipulation ? If you are still confused with this ‘term’, let me explain it to you. Actually, the data collection process can have many loopholes. At times, this stage is also known as data wrangling or data cleaning. Different Ways to Manipulate / Treat Data: There is no right or wrong way in manipulating data, as long as you understand the data and have taken the necessary actions by the end of the exercise. Usually, beginners on R find themselves comfortable manipulating data using inbuilt base R functions. #or
Future Climate for Africa (FCFA) Climate plays a significant role in the lives of many people in Africa; the majority of livelihoods of African people depend on rain-fed agriculture and in some areas, water resources are increasingly stressed. Sub-Saharan Africa is the only region where vulnerability to weather extremes is rising, and the intensity of climate hazards is expected to rise over the coming decades (IPCC, 2013)[1]. Without climate risk management and adaptation, the progress made against the Millennium Development Goals will increasingly come under threat in Africa (OECD, 2009)[2]. High-quality climate information is a crucial foundation for effective climate risk management and adaptation; yet this is not available and not used across many parts of sub-Saharan Africa. The aim of the FCFA research programme is therefore to support research to better understand and improve confidence in predictions of climate variability and change across sub-Saharan Africa on timescales to inform adaptation.
TinkerPop Introduction to Principal Component Analysis (PCA) - Laura Diane Hamilton Principal Component Analysis (PCA) is a dimensionality-reduction technique that is often used to transform a high-dimensional dataset into a smaller-dimensional subspace prior to running a machine learning algorithm on the data. When should you use PCA? It is often helpful to use a dimensionality-reduction technique such as PCA prior to performing machine learning because: Reducing the dimensionality of the dataset reduces the size of the space on which k-nearest-neighbors (kNN) must calculate distance, which improve the performance of kNN. Reducing the dimensionality of the dataset reduces the number of degrees of freedom of the hypothesis, which reduces the risk of overfitting. What does PCA do? Principal Component Analysis does just what it advertises; it finds the principal components of the dataset. Can you ELI5? Let’s say your original dataset has two variables, x1 and x2: Now, we want to identify the first principal component that has explains the highest amount of variance.
worldpoliticsreview Observers of China’s engagement with Africa often assume that Africa is passive in the relationship. A look at Mozambique, Zimbabwe and South Africa shows that the reality is more complicated: Chinese actors often try to partially adapt to specific African systems, with varying degrees of success. Chinese investment and engagement now touches almost every aspect of Africa’s economy, including infrastructure, transport and logistics, trade, manufacture, agriculture, telecommunications and, of course, resource extraction. Because of the vastness of this engagement, commentators frequently fall back on catchall concepts, including an assumption that Africa is essentially passive in this relationship. The reality is much more complicated.
Downloadable Sample SPSS Data Files Downloadable Sample SPSS Data Files Data QualityEnsure that required fields contain data.Ensure that the required homicide (09A, 09B, 09C) offense segment data fields are complete.Ensure that the required homicide (09A, 09B, 09C) victim segment data fields are complete.Ensure that offenses coded as occurring at midnight are correctEnsure that victim variables are reported where required and are correct when reported but not required. Standardizing the Display of IBR Data: An Examination of NIBRS ElementsTime of Juvenile Firearm ViolenceTime of Day of Personal Robberies by Type of LocationIncidents on School Property by HourTemporal Distribution of Sexual Assault Within Victim Age CategoriesLocation of Juvenile and Adult Property Crime VictimizationsRobberies by LocationFrequency Distribution for Victim-Offender Relationship by Offender and Older Age Groups and Location Analysis ExamplesFBI's Analysis of RobberyFBI's Analysis of Motor Vehicle Theft Using Survival Model