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

The R Trader » Blog Archive » BERT: a newcomer in the R Excel connection A few months ago a reader point me out this new way of connecting R and Excel. I don’t know for how long this has been around, but I never came across it and I’ve never seen any blog post or article about it. So I decided to write a post as the tool is really worth it and before anyone asks, I’m not related to the company in any way. BERT stands for Basic Excel R Toolkit. It’s free (licensed under the GPL v2) and it has been developed by Structured Data LLC. At the time of writing the current version of BERT is 1.07. 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:

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. This would also be the focus of this article – packages to perform faster data manipulation in R.

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.

Average Annual Percent Change (AAPC) — Joinpoint Help System 4.3.1.0 While Joinpoint computes the trend in segments whose start and end are determined to best fit the data, sometimes it is useful to summarize the trend over a fixed predetermined interval. The AAPC is a method which uses the underlying Joinpoint model to compute a summary measure over a fixed pre-specified interval. Annual Percent Change (APC) is one way to characterize trends in cancer rates over time. With this approach, the cancer rates are assumed to change at a constant percentage of the rate of the previous year. Geometric standard deviation In probability theory and statistics, the geometric standard deviation describes how spread out are a set of numbers whose preferred average is the geometric mean. For such data, it may be preferred to the more usual standard deviation. Note that unlike the usual arithmetic standard deviation, the geometric standard deviation is a multiplicative factor, and thus is dimensionless, rather than having the same dimension as the input values. Definition[edit]

Manuali di Statistica Lamberto Soliani con la collaborazione di Franco Sartore e Enzo Siri Interactive Statistical Calculation Pages Plot Digitizer D3.js

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