Probability Distributions

In summary, if you're struggling with understanding probability and distributions, there are many helpful resources available such as Khan Academy, textbooks, and online courses that can provide clear explanations and practice problems to improve your understanding.
  • #1
fasterthanjoao
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1
Basically, I'm having some difficulty grasping some of the concepts in probability.

..At first I was writing details of what my lecturer has given me, but really I can't make much sense of it and it'd be foolish to type it all out here.

The jist of work is really just as follows; we've been doing basic work on different kinds of distributions: gaussian, poisson and discrete distributions (how the distributions arise and what they're good for etc) and the notes I'm following are pretty bad, I've got a basic physics textbook but its not really much help in this area since its really just maths and really what I'm asking is does anyone know where I can get some good notes on basic info about distributions and errors (uncorrelated error propagations etc..)?

I've tried googling and I'm finding random stuff that's useful, but yeah.

c'mon..

thanks.
 
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  • #2
One of the best places to look for help with probability and distributions is Khan Academy. They have a series of videos and interactive exercises on probability, distributions, and errors. Additionally, they have a forum where you can ask questions and get help from other students and experts. Another great resource is the book Probability and Statistics for Engineers and Scientists by Sheldon M. Ross. This book provides an introduction to the concepts and tools for understanding probability and statistics, and it includes numerous examples and exercises. Finally, there are a number of online courses available through MOOCs (Massive Open Online Courses) that can provide a more in-depth look at probability and distributions. Coursera and edX are two of the most popular platforms for these courses.
 
  • #3


I can understand your struggle with grasping concepts in probability distributions. It can be a challenging topic to grasp, but it is an essential aspect of scientific research and analysis. I would suggest seeking out additional resources such as textbooks, online tutorials, or even consulting with a statistics expert to get a better understanding of the concepts. It's also important to practice working through problems and examples to solidify your understanding. Don't get discouraged, probability distributions are a complex topic, but with dedication and perseverance, you will be able to master them.
 

What is a probability distribution?

A probability distribution is a mathematical function that shows the possible outcomes of a random event and the likelihood of each outcome occurring. It is used to describe the probability of different outcomes within a sample space.

What are the types of probability distributions?

There are two main types of probability distributions: discrete and continuous. Discrete distributions are used when the possible outcomes are countable, while continuous distributions are used when the possible outcomes are uncountable.

What is the difference between a probability distribution and a probability density function?

A probability distribution is a function that assigns probabilities to each possible outcome, while a probability density function is a function that describes the relative likelihood of each outcome in a continuous distribution. In other words, a probability density function is the derivative of a probability distribution.

How is a probability distribution represented?

A probability distribution can be represented in several ways, including a graph, a table, or a mathematical equation. Graphs, such as histograms, are often used to visually represent the distribution of data, while tables and equations are used to calculate and describe the probabilities of each outcome.

What is the purpose of using a probability distribution in statistics?

Probability distributions are an essential tool in statistics as they allow us to analyze and interpret data, make predictions, and calculate probabilities. They also help us understand the underlying patterns and behaviors of random events, which can be useful in various fields, including science, finance, and engineering.

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