# Class 12 Maths Chapter 7 Probability Distributions

Maharashtra State Board, Class 12 Mathematics & Statistics-2 (Arts & Science) Chapter 7 Probability Distributions is an important chapter. In this chapter, there are three exercises that are exercise 7.1 Probability Distributions, Exercise 7.2 Probability Distributions and Probability Distributions Miscellaneous Exercise 7. The students who are studying in class 12 of Maharashtra state Board and want to score more marks in the final examination, need to go through our Pdf solutions once.

Below, we provide free Pdf solutions for this chapter 8 Binomial Distribution.

Chapter-7-Probability-Distributions

## Maharashtra Board Class 12 Maths Chapter 7 Probability Distributions answers in Pdf

As we discussed above that, we are providing you with free Pdf solutions for the exercise 7.1 and exercise 7.2 and Exercise 7 of the Chapter 7 Probability Distributions in Pdf. If you want to score good marks in the final examinations, you need to download our Pdf solutions. Our Pdf solutions are prepared by the expert teachers who have more to twenty years of teaching experience.

### std 12th Chapter 7 Probability DistributionsEx. 7.2

std 12th Chapter 7 Probability Distributions Ex.7 Miscellaneous

## Understanding the Concept of Probability Distributions :

Probability distributions are an important concept in mathematics that are used to describe the behaviour of random variables. A random variable is a variable that can take on different values based on the outcome of a random event. For example, the number of heads that occur when flipping a coin three times is a random variable, as the outcome (the number of heads) is not fixed and can vary.

There are several different types of probability distributions, including discrete distributions and continuous distributions.

Discrete probability distributions are used to model the probability of a specific number of successes occurring in a fixed number of trials. An example of a discrete probability distribution is the binomial distribution, which is used to model the probability of a certain number of "successes" occurring in a fixed number of "trials".

Continuous probability distributions, on the other hand, are used to model the probability of a continuous range of values. An example of a continuous probability distribution is the normal distribution, which is often used to model the distribution of continuous data, such as the heights of people in a population.

In order to determine the probability distribution of a random variable, you must first determine the possible values that the random variable can take on and the corresponding probabilities for each of those values. For example, if you were rolling a six-sided dice, the possible values of the random variable (the number of spots on the dice) would be 1, 2, 3, 4, 5, and 6, and the probability of each of those values occurring would be 1/6.

Probability distributions are an important tool in various fields, including biology, economics, and engineering. They can be used to model the probability of certain outcomes occurring, such as the probability of a certain number of defective items in a batch of products or the probability of a certain number of patients experiencing a certain side effect after taking a certain medication.

## Importance of Chapter 7 probability distributions of Class 12 Mathematics & Statistics-2 (Arts & Science)

Chapter 7 of Class 12 Mathematics & Statistics-2 (Arts & Science) deals with probability distributions. Probability distribution refers to the set of possible values and the corresponding probabilities of the possible outcomes of a random event.

There are two types of probability distributions: discrete and continuous. Discrete probability distribution refers to the probability distribution of a discrete random variable, which can take on only a countable number of values. Examples of discrete probability distributions include binomial distribution and Poisson distribution. Continuous probability distribution refers to the probability distribution of a continuous random variable, which can take on any value within a certain range. Examples of continuous probability distributions include normal distribution and exponential distribution.

In this chapter, students will learn about the various probability distributions and their properties. They will also learn how to find the mean, variance, and standard deviation of a probability distribution and how to use these measures to describe the distribution.

Additionally, students will learn about the application of probability distributions in real-life situations, such as finding the probability of an event occurring in a given time period or the probability of a product meeting certain specifications.

Overall, understanding probability distributions is essential for data analysis and decision-making in various fields, including finance, engineering, and the social sciences.