5.1Probability Basics
uncertainty is inherent in inferential statistics, because there is always the need to estimate the overall sample, The science of uncertainty is called probability theory. Learn probability distributions help us through the sample overall analysis of the relevant data ( EG , Mean ...)
Basically, by an experiment, we mean an action whose outcome cannot be predicted with certainty
By an event, we mean some specifified result that may or may not occur when an experiment is performed
More generally, the frequentist interpretation of probability construes the probability of an event to be the proportion of times it occurs in a large number of repetitions of the experiment. ( Which uses probability represents an event (ie, a large number of repeat experiments sample in a large number of repeat Test ) the occurrence rate)
Two different sets of coin toss experiment, the number of the plurality of samples is 100 , the frequency of each calculation relevant sample side up, i.e. the first 100% ( 1/1 ), the second 50% ( 1/2 ), third 33% ( 1/3 ), etc.
Although the frequentist interpretation is helpful for understanding the meaning of probability, it cannot be used as a defifinition of probability. One common way to defifine probabilities is to specify a probability model—a mathematical description of the experiment based on certain primary aspects and assumptions.
Thus, for example, assume that a coin is tossed binomial distribution
Equal-likelihoodpuv Model of The : Assume that the probability of each result (different) occurs.
The equal-likelihood model discussed earlier in this section is an example of a probability model. Its primary aspect and assumption are that all possible outcomes are equally likely to occur. We discuss other probability models later in this and subsequent chapters
