Google Analytics Trick: See The Full Referring URL If you use Google Analytics to track your websites stats, you have probably realized that Google doesn’t let you see the full URL of the sites referring traffic to you. That’s a basic feature that somehow is not included in GA but fortunately for us, there is a simple trick you can implement to display the full URL of the referring site. Before I explain you this trick, let me give full credit to Ruben Yau for actually coming up with it. As stated above, Google Analytics doesn’t let you see from what specific page your visitors are coming. For example, instead of showing this as the traffic referrer: it will just show you this: Digg.com That’s not very useful information… The solution to view the full URL of the referring site is to implement a simple hack that uses filters to place the referrer into the User Defined Report. It should look like this: Now, if you look at your Traffic Sources, you usually see this:
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
Research Blog 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.
LingPipe Home How Can We Help You? Get the latest version: Free and Paid Licenses/DownloadsLearn how to use LingPipe: Tutorials Get expert help using LingPipe: Services Join us on Facebook What is LingPipe? LingPipe is tool kit for processing text using computational linguistics. Find the names of people, organizations or locations in newsAutomatically classify Twitter search results into categoriesSuggest correct spellings of queries To get a better idea of the range of possible LingPipe uses, visit our tutorials and sandbox. Architecture LingPipe's architecture is designed to be efficient, scalable, reusable, and robust. Java API with source code and unit tests; multi-lingual, multi-domain, multi-genre models; training with new data for new tasks; n-best output with statistical confidence estimates; online training (learn-a-little, tag-a-little); thread-safe models and decoders for concurrent-read exclusive-write (CREW) synchronization; and character encoding-sensitive I/O.
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.
How Your Data Can Predict The Future 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 Top 5 Ways to Use British Airways Avios Points - Extra Pack of Peanuts Posted By Trav Now that you’ve read the 4 Things You Should Know about British Airways Avios Points (if you haven’t, check it out first) and are up to speed with the program, let’s look at the top 5 ways to use your Avios points. As I’ve mentioned many times before BA points can be incredibly valuable, but ONLY if you used in very specific circumstances. Therefore, it is even more important with BA than with other airlines to know which circumstances give you the best bang for your buck because if you use them wrong, you could end up paying HUGE fuel surcharges…and nobody wants that! If you’ve already got a nice stash of BA Avios points, great! If you want to start building up your balance, grab the Chase British Airways Visa (which can be found on the Best Current Deals page or the Airline Credit Card page). Then, use those points in the following ways: 1. Using Avios points for short haul domestic flights can offer some incredible value. Only 4,500 points? 2. Examples 3. 1. 2. 4. 5.