In statistical courses, we study the probability distributions and among the best known are Normal Distribution, Binomial and Poisson Distribution. Each with its own characteristics, which can identify, including the Binomial distribution can be approximated by the normal distribution. The students, in presenting the evidence generally have difficulty identifying which probability distribution should be applied to obtain the result. Perhaps the easiest is the Normal distribution, because in the problem statement indicating there are phrases such as the distribution of data. A normal distribution of random variables is continuous, meaning that the measured magnitudes take any real value (eg the amount of rain that falls in Caracas in one month). Binomial Distribution and Poisson distributions are discrete random variable, which are those that assume a countable set of values. (Example: the number of students passing an exam) The set of problems Normal distribution, generally expressed that the data follow the normal distribution and the data given as mean values and standard deviation values necessary to standardize the variable and find the probability in the table. Now, to identify a problem of Binomial Distribution, observe if the event or experiment has two outcomes, whether or not success or failure, on or off, that events are independent and that the probability remains fixed during the experiment.

Typical Statements: probability is born male or female, catch a thief, defective parts. And finally a Poisson distribution describes independent events occurring in a given space or a constant rate over time. It is important to clarify that the unit of measurement is continuous (time, area) but the random variable is discrete (number of accidents, number of calls) have clear features of the different distributions of aid when solving problems. I recommend reading several statements and before any calculation, identify the characteristics of the distributions. There are videos with problems solved step by step and where you can identify the characteristics of the distributions,.