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What is the probability calculator

What Is The Probability Calculator

Probability Calculator

Probability Calculator is an online application that assists in determining the likelihood of an event occurring. There are two sorts of probability: experimental probability and theoretical probability. Probability is utilized in a variety of businesses to create predictive mathematical models.

The probability calculator calculates the likelihood of an event occurring by dividing the favourable outcomes by the total outcomes. Probability is a branch of statistics describing an event's likelihood.

Binomial Probability Calculator

A binomial probability calculator is a free online application that calculates the binomial probability of an occurrence. The binomial distribution calculator can assist you with questions such as: What is the likelihood of a given number of successes in a series of events?

Binomial probability is defined as the likelihood of achieving an exact number of successes in an exact number of tries. We use the following formula to calculate the binomial probability:

b(r; n, P) = nCr × Pr × (1 – P)n – r

Here, b denotes the binomial probability, n is the number of tries, r is the number of successes, and P is the probability of a single trial succeeding.

Probability Distribution Calculator

The Probability Distribution Calculator is a tool that allows you to calculate critical values for a given distribution based on user-specified parameters, degrees of freedom, or significance levels. The interactive graph icons, which display the density function and cumulative distribution function for the given distribution dependent on the relevant parameters, are one of the calculator's distinguishing features. Those graphs can be displayed in the conventional (customizable) graph window and printed using the Create Graph option. This calculator can be used using the Probability Calculator option in the Basic Statistics and Tables Startup Panel, which can be accessed through the Statistics tab, Base group (ribbon bar), or Statistics menu (classic menus).

Normal distribution probability calculator

The normal distribution (sometimes known as the Gaussian distribution) is a continuous probability distribution. Most of the data is near a centre value, with no bias to the left or right. This distribution follows many natural observations, such as human height or blood pressure.

The mean value (average) of a normal distribution is also the median (the "middle" number in a sorted list of data) and the mode (the value with the highest frequency of occurrence). Because this distribution is symmetric about the centre, 50% of the values are less than the mean, and 50% are more than the mean.

This normal distribution calculator (also known as a bell curve calculator) computes the area under a bell curve and determines the likelihood that a number is more or less than any arbitrary value X. You may also use this probability distribution calculator to determine the likelihood that your variable falls within any arbitrary range, X to X2, simply by entering the normal distribution mean and standard deviation values.

To begin with, a normal probability distribution is a continuous probability distribution that can take random values across the entire real line. The following are the main characteristics of the normal distribution:

  • As it is continuous, the probability of obtaining any single, specific outcome is nil.
  • It has a "bell-shaped" distribution, which gives rise to the term "Bell-Curve."
  • Two parameters determine the normal distribution: the population mean and the population standard deviation.
  • It is symmetric in relation to its mean.

How to find probability by using a probability calculator

The theoretical probability formula is as follows:

Theoretical probability = the number of positive outcomes divided by the total number of outcomes.

Some hypotheses are followed by both theoretical and experimental probability. These are listed below:

  • Any event's probability will always be greater than or equal to zero.
  • The sample space represents the collection of all possible outcomes for the event.
  • Assume we have two events, A and B, that cannot occur concurrently. The likelihood of A or B occurring is provided by the sum of the probabilities of A and B. Such events are also known as mutually exclusive events.

The following are the probability rules:

  • The null set is used to represent the likelihood of an impossible event.
  • The likelihood of an event occurring ranges from 0 to 1.
  • A negative probability cannot exist for an occurrence.
  • The chance of an event occurring and not occurring is determined by 1.

How to find probability in statistics

The probability formula expresses the possibility of an event occurring. The formula for calculating an event's probability is the ratio of positive outcomes to the total number of outcomes. Probabilities are always between 0 and 1. The generic probability formula is as follows:

Probability = Number of Favorable Outcomes / Total Number of Outcomes


P(A) = f / N


  • P(A) = probability of an event (event A) occurring
  • f= number of ways an event can occur (frequency)
  • N= Total number of outcomes possible

Here are the steps to determine single-event probability:

The following are the stages to determining single-event probability:

  1. First, identify a single occurrence that has a single outcome.

The first step in solving a probability problem is deciding how much probability to calculate. This can be an event, such as the likelihood of rain on a Wednesday or rolling a specific number on a die. There should be at least one conceivable consequence to the occurrence.

For example, if you wish to calculate the likelihood of rolling a "3" with a die on the first roll, you'd find that there is only one positive outcome: you roll a "3."

  1. Identify the total number of outcomes that can occur

Next, you need to determine the number of outcomes that can occur from the event you identified in step one. In the example of rolling a die, six total outcomes could occur because there are six numbers on a die. So for the single event—rolling a "3" on the first roll—there may be six different outcomes that can occur.

  1. Determine the total number of possible outcomes

Next, you must determine the number of possible outcomes from the event you identified in step one. For example, in the case of rolling a die, there are six possible outcomes because there are six numbers on a die. So, there are six possible outcomes for a single event—rolling a "3" on the first roll.

  1. Subtract the number of occurrences from the total number of possible outcomes

Divide the number of ways the event can occur by the number of possible outcomes after determining the probability event and its corresponding consequences. For example, rolling dice once and landing on the number "3" is considered one event.

You can continue to roll the die and record the results, but each roll will be treated as a separate event. In the case of this die, you would divide the single occurrence by the six possible outcomes:

  • This yields a fraction: 1/6.
  • The odds of rolling a "3" on the first try are one in six.

How to find probability distribution?

Here are some of the Probability Distribution formulas based on their types. 

The Formula for the Normal Distribution


μ = Mean Value

σ =Standard Deviation

x= Normal random variable

If mean μ = 0, and standard deviation =1, then this distribution is termed Normal Distribution.

The Formula for the Binomial Distribution


n=Total number of events

r = Total Number of successful events

p = successful on a single trial Probability,

1-p = Failure Probability

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