# What is onomatopoeic words and its examples?

## What is onomatopoeic words and its examples?

Onomatopoeia words are commonly used in comic strips and comic books. Onomatopoeia, what a word! It means every sound effect you’ve ever heard. Ding, dong, ping, pong, clank, swoosh, crash, bang, crunch, zip, munch and sizzle. Crackle, hiss, zap, oink, splat, whiz, moo and achoo.

### Is tap an example of onomatopoeia?

In one of his most famous works, ‘The Raven,’ Edgar Allan Poe wrote, ‘While I nodded, nearly napping, suddenly there came a tapping, As of some one gently rapping, rapping at my chamber door…’ In this line the words ‘rapping, rapping’ are onomatopoeia because they mimic the sound that the bird was making on the door.

#### Is flutter an onomatopoeia?

An onomatopoeia is a very special thing. It’s a word like quack or flutter, or oink or boom or zing. It sounds just like its meaning, for example snort and hum.

Is fart an onomatopoeia?

Well, not only have many comics simply used “FART!” as a sound effect, but the word is also, probably, an onomatopoeia (though, given the fact that the word is about 700 or 800 years old, it’s hard to trace its exact origin).

Is Yum an onomatopoeia?

Some theorists include some exclamations (yummy!) and interjections (hey!) in a category of onomatopoeia, although note that the border between exclamations and interjections is very fuzzy.

## What is an example of a stochastic process?

A bacterial population growing, an electrical current fluctuating due to thermal noise, or the movement of a gas molecule are all common examples. Stochastic processes are commonly used as mathematical models of systems and phenomena that appear to vary randomly.

### When does a stochastic process reach state E0 before en?

Finally, if the process is at stateEk,0

#### Is a stochastic process discrete or continuous?

Yes, generally speaking, a stochastic process is a collection of random variables, indexed by some “time interval” T. (Which is discrete or continuous, usually it has a start, in most cases t 0: min T = 0 .) But it also has an ordering, and the random variables in the collection are usually taken to “respect the ordering” in some sense.

How do you find the time of a stochastic process?

1) Find the stochastic matrix. 2) Prove that the Markov chain is irreducible. 3) Find the invariant probability vector. 4) Check if the Markov chain is regular. 5) To time t =0 the process is in stateE1.DenotebyT1the random variable, which indicates the time of the rst return toE1. Compute P {T1= k} ,k=2, 3, 4, 5, and nd the mean ofT1.

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