Bayes’ theorem

Probability is defined as the ratio of the number of favourable outcomes to the total number of possible outcomes of an event. In an experiment with ‘n’ number of outcomes, the number of favourable outcomes can be stated as x. The formula for calculating the probability of an event is as follows. Probability (Event) = […]

The degree of an event’s chances is referred to as its probability. There must be some probability attached to an event as it happens, such as when a ball is thrown, a card is drawn, etc. Probability in mathematics is defined as the proportion of desired outcomes to all potential outcomes.  Given that the first

The addition rule for probabilities consists of two separate rules or formulas. The first rule takes into account the occurrence of two events that are incompatible with one another, while the second rule takes into account the occurrence of two events that are compatible with one another. The fact that the two events in question

In order to give probabilities to a collection of probable values, a random variable must be measured as a function. Clearly, the consequences depend on a number of unforeseeable physical elements. For instance, the outcome of a fair coin flip will be determined by the physical conditions. It is impossible to determine which outcome will

What exactly is Exponential Distribution? The exponential distribution is a continuous probability distribution in probability theory and statistics that often concerns the amount of time until a given event occurs. It is a continuous and independent process in which events occur at a constant average pace. The important feature of the exponential distribution is that

Probability refers to the probability of a specific event occurring. A probability has a number between 0 and 1, indicating that if an event is impossible, the probability is 0 and if it is certain, the probability is 1. Experimental probability is defined as the probability calculated from the findings of an experiment. Empirical probability

Exhaustive events are a series of occurrences in a sample space that occur compulsorily while doing the experiment. In layman’s terms, all potential occurrences in a sample space of an experiment represent exhaustive events. For example, there are two conceivable outcomes when flipping an impartial coin: heads or tails. As a result, these two possibilities

A set of results from a random experiment can be used to describe events in probability. The sample space represents every scenario that could occur during an experiment. As a result, in probability, occurrences can also be thought of as parts of the sample space. Probability encompasses a wide variety of event kinds. Each type

One key aspect of probability is that it can only be applied to trials in which the complete number of outcomes is known, i.e., the idea of probability cannot be applied unless and until the total number of outcomes is known. To apply probability in everyday settings, we must first understand the entire number of

Hypothesis testing is a technique for drawing statistical conclusions from population data. It’s a tool for analysing assumptions and determining how likely something is based on a set of criteria. Hypothesis testing is a method of determining whether or not the outcomes of an experiment are accurate. Before doing hypothesis testing, a null hypothesis and