Random Country

What is the biggest country in the world?

The biggest countries in the world are (from largest to smallest in size) Russia, Canada, China, the United States, Brazil and India. Russia is the largest country in the world. It is twice the size of Canada and about four times the size of the United States. It covers more than one-eighth of Earth's land area and is larger than the next nine largest countries combined. Canada is the second largest country in the world. It covers more than nine million square kilometers (3.5 million square miles, or almost 1.5 times the size of the United States. China is the third largest. It covers nearly 9.6 million square kilometers (about 3.7 million square miles, or almost twice the size of the United States. The United States is the fourth largest country in the world. It covers 9.4 million square kilometers (3.7 million square miles, or more than 1.5 times the size of Russia. Brazil is fifth largest, covering nearly 8.5 million square kilometers (about 3.2 million square miles, or about 1.2 times the size of the United States. India is the sixth largest country in the world. It covers 7.3 million square kilometers (about 2.8 million square miles, or about 1.2 times the size of the United States. Other large countries include Argentina, Canada, Australia, China, Indonesia, Kazakhstan, Mexico, and Russia.

What is a country?

A country is a territory, constituting a geographical and human entity. It is characterized by one or more oral and written languages used by the inhabitants of the country. Some countries have come together to form groups like the European Union. Others divide after conflicts or power grabs.

Random Word Generator

The Random Word Generator is a tool to help you create a list of random words. The tool generates random words for you to use in your writing or other creative projects.

Random in Computers

Computers can generate truly random numbers if given a source of entropy. This is used in cryptography where truly random numbers are needed, for example for creating encryption keys. Computers can also be used to simulate random events. By generating a series of random numbers from a stochastic process, like a Poisson process or a Markov process, a simulation of the process itself can be obtained. This is used in computer animation for the generation of natural looking phenomena, for example the way water flows in a stream. Random number generation is also used in statistical sampling to generate a representative sample from a population. If a sequence of numbers is naively generated from a true random number generator, the numbers may appear to have a pattern. The period of this pattern is the length of the seed number used. Once the whole seed number has been used, the sequence repeats. Since computers can only store and manipulate numbers as a discrete set of values, in practice all computer-generated random numbers are random. That is, each number is associated with a specific algorithm and stream of data, and the characteristics of that data affect the numbers generated. In other words, the sequence of numbers is determined by the program, which is a deterministic process. The problem is that if the algorithm is not truly random, it is possible, by examining the patterns in the sequence of numbers, to predict future values in the sequence. This is a form of statistical attack. This can be countered by changing the seed number periodically. With each new seed, a different sequence is started, which as far as is known, has an unpredictable pattern. This is exactly what is done for the sequences in many types of random number generators, including those used in computer graphics and games. In these applications, the sequence of numbers is usually displayed. Anyone who knows the algorithm can then "re-seed" the generator, with the seed number found from the sequence, and thus generate the same sequence of numbers. In computer graphics, this is not considered a problem, as what is being displayed is the pattern, not the numbers. In cryptography and computer security, however, it is a problem, since an attacker can use such a sequence of numbers to predict future values. random numbers are random enough for most practical purposes. For example, they may be used in simulations involving games of chance, like poker or blackjack. The random numbers are used to determine the outcome.