We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Exponential distribution is a continuous distribution that models random time between events (until next event occurs) during a Poisson process, which is a process with constant occurrence rate Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Normal distribution is a continuous random variable distribution with bell-shaped probability density curve. It is widely used in statistical data analysis, and the basis for many other distributions Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Continuous Uniform distribution is used to model a flat probability existence with a range (A,B). Its probability density can be depicted as The follow figure shows probability density Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Poisson distribution is used to model the random number (x) of event occurrence during a Poisson process, which focus on the occurrence of same random events during a Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Negative binomial distribution is used to model the particular probability of k-th success occurring at x-th Bernoulli trial, which is equivalent to say that it has experienced x-1 Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Hypergeometric distribution is connected with taking n items (no replacement) from N items, where k items labeled success and N-k items failure. The success number x of n Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Binomial distribution in statistics is a type of discrete probability distribution, modeling the probability of success times among a predetermined Bernoulli process. A Bernoulli process is a binary Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! R provides rich availability of using probability functions. Probability functions in R takes the form [dpqr][prob], Where [dpqr] represent which kind of variates the function works on d – Read more…
n this post, we show how to generate random numbers into vector and matrix in R programming, from various statistical distributions. Specifically, we focus several basic and widely used statistical distributions here, namely, normal distribution, continuous uniform distribution, binomial distribution and Poisson distribution.
It is not uncommon to generate random sequences in R programming. sample() function provides the feasibility of generating such random objects from given vectors, either with or without replacement. The following code shows an example that 32 numbers with replacement drawn from 50 integers from 1 to 50.