Contains all the articles of the site

All users of Google Analytics end up suffering the attacks of a legion of referral spam bots that distorting all data obtained from your website, this traffic can come to represent an amount much higher than the actual traffic visits.

In this article I explain how to remove all traffic of this type definitively from our statistics.

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POD (Portal Open Data) is a project that I started when I was studying to obtain Microsoft Web Developer MCSD, in order to do some practices. Consists of a SQL Server database through which on can access to other databases in a centralized way.

In this article I describe the POD Configuration database

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From this page you can download an installable copy of the POD Configuration database. You can find also instructions to install and setup it on the server, and to download a free version of SQL Server.

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In this page you can download the central PISA database, which contains all the common data for all countries, as questions, response values and territorial divisions.

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In this page you can find the instructions and the links to download and install each PISA national database with the responses of students, schools and parent questionaires of the years from 2000 to 2012.

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PISA (Program for International Student Assessment) is a program of the OECD (Organization for Economic Cooperation and Development) for the evaluation of education policies. It consists of a series of tests and surveys conducted to 15 years old students, schools and parents at national level in the countries participating in the program (in 2012 there were 65 participating countries, and in 2015 there are more than 70). These tests seek to assess the level of knowledge in three main areas: Reading, science and math.

In this article I make a brief introduction to SQL Server database created from the original data published by the OECD.

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In previous articles I have talked about the POD project, a database that centralizes access to other databases so that they can be consulted through a common interface. In this article we will see the tool that is used for data filtering and query on any of the databases integrated into POD.

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In the previous article we saw how to query POD databases with the WinPODUtil program, in this article we will see how to use the tool to process the CSV files generated by the queries, or any other CSV file. The format of these files consists in a series of text lines, the first of which must contain the column headings, separated by the semicolon character (;). Each line, except the first, represents one data record.

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Every three years, since 2000, the OECD (Organization for Economic Cooperation and Development) performs a series of tests in a number of countries at national level to 15-years-old students, in order to assess the degree of knowledge in three main groups of areas: science, reading and math. This is the PISA program, whose last edition took place in 2015.

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In this post you will find examples of R code for data sampling in PISA database. In these examples the different weights of students, schools or parents are corrected depending on the number of records selected for the sample. Also there are examples of stratified sampling using the values in a particular column in the data set.

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In the previous article in this series we saw an introduction to PISA data analytics, with examples of functions in R code for sampling, and we talked about the sampling weights, which ponder each student so that it represents a group of individuals with the same characteristics rather than a single student, (remember that PISA aims to assess the effect of educational policies on the whole population of the country, not on individual students). In this article, we will see how to use these weights to calculate estimators from samples and we'll see also how to calculate standard errors of these estimators using replicated weights.

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In this post you can download the R code examples to compute the standard errors of the mean, standard deviation, proportions or mean differences, on the data of the PISA database, using the replicate weights method.

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In the previous article in this series we viewed how to computing standard errors with replicate weights in PISA database, in this article we will take an overview of one of the most controversial points of these studies, the complex system of scores implemented.

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In this post you can download the R code samples to work with plausible values in the PISA database, to calculate averages, mean differences or linear regression of the scores of the students, using replicate weights to compute standard errors.

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The catalog views contain all the information concerning the structure of the database: schemas, tables, table fields, data types of the fields, integrity constraints, stored procedures code, etc. The knowing of them is essential to develop tools for data management independent of the structure. In this article we will view an example of one of these tools, DBTextFinder, a simple application that will allow us to search for text in the records of our database and within the code of the views and stored procedures.

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Usually, when you perform a data analysis, you suppose that they come from a normal distribution. In fact, you perform a battery of tests to verify that this assumption is met and, otherwise, you try to modify the data so that it is satisfied. This is because most analysis techniques only work properly on normally distributed data. But there are a number of systems that present a complex dynamics where is not valid to apply this hypothesis and wherein adjusting the data only leads to distortions that invalidate the results.

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In many applications it is necessary to generate random numbers. To do so, the .NET framework provides the Random class, which can generate uniformly distributed pseudo-random values, which means that all numbers are equally likely to appear in the result. But in some cases we need to generate random values that follow other different types of distribution. In this article we will see how to generate random numbers that follow a normal distribution, with a system that can be extended to any other type of distribution.

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Currently there are a lot of video capture devices commercially available; anyone can buy a digital camera or a webcam at a reasonable price. All of these devices can be easily controlled from a program developed by ourselves using Microsoft DirectShow. DirectShow is a set of interfaces that provide a generic API with which you can capture and play audio and video regardless of the brand or model of camera you are using. It also allows recording and playback of files in any format.

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In the previous article in this series, I did a summary of the basic components of DirectShow: filters, filter graphs and pins to connect the elements together, and how we can identify them using the GraphEdit tool of the SDK. In this article I will show how to build a "simple" application to capture and playback video using the interfaces provided in DirectShow, a subset of the COM distributed object model from Microsoft.

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Many of the network IP cameras that can be found on the market use the Netwave protocol, based on CGI commands to obtain video images through an internal http server. In this article I will show how to build a simple application to control these cameras, which are typically used for surveillance and can make scan motions in addition to providing video images.

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