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Polynomial vs non polynomial time complexity

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Q: What is the difference between polynomial and non polynomial time complexity?
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What is the difference between exponential and polynomial time complexity?

Algorithms which have exponential time complexity grow much faster than polynomial algorithms. The difference you are probably looking for happens to be where the variable is in the equation that expresses the run time. Equations that show a polynomial time complexity have variables in the bases of their terms. Examples: n^3 + 2n^2 + 1. Notice n is in the base, NOT the exponent. In exponential equations, the variable is in the exponent. Examples: 2^n. As said before, exponential time grows much faster. If n is equal to 1000 (a reasonable input for an algorithm), then notice 1000^3 is 1 billion, and 2^1000 is simply huge! For a reference, there are about 2^80 hydrogen atoms in the sun, this is much more than 1 billion.


What is polynomial complexity?

That means that the running time of a program is proportional to some power of the input size.


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The difference between multicollinearity and auto correlation is that multicollinearity is a linear relationship between 2 or more explanatory variables in a multiple regression while while auto-correlation is a type of correlation between values of a process at different points in time, as a function of the two times or of the time difference.


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