It is still an open question. NP is the class of problems which can be solved in polynomial time by a program run by the theoretical non-deterministic machine. (That is, there is a polynomial upper-bound for the time it would take for the machine to compute the answer, with respect to the size of the input).
P is the class of problems which can be solved in polynomial time by a program run by an actual computer (or some abstract model thereof).
So far it is not known for sure whether the two classes are the same or not. There are many problems which are known to be NP, and for which no polynomial solution for a real computer is known. However, there is currently no proof that such a solution does not exist (perhaps it does and no one has found it yet). That is why whether P equals NP or not is still an open problem.
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Comparative operators are used to compare the logical value of one object with another and thus establish the rank (ordering) of those objects. There are six comparative operators in total: p<q : evaluates true when p is less than q p>q : evaluates true when p is greater than q p<=q : evaluates true when p is less than or equal to q p>=q : evaluates true when p is greater than or equal to q p!=q : evaluates true when p is not equal to q p==q : evaluates true when p is equal to q
A PA is a Physician Assistant, the C means that a national certification exam was taken and passed. An NP is a Nurse Practitioner.
The relational operators: ==, !=, =.p == q; // evaluates true if the value of p and q are equal, false otherwise.p != q; // evaluates true of the value of p and q are not equal, false otherwise.p < q; // evaluates true if the value of p is less than q, false otherwise.p q; // evaluates true if the value of p is greater than q, false otherwise.p >= q; // evaluates true of the value of p is greater than or equal to q, false otherwiseNote that all of these expressions can be expressed logically in terms of the less than operator alone:p == q is the same as NOT (p < q) AND NOT (q < p)p != q is the same as (p < q) OR (q < p)p < q is the same as p < q (obviously)p q is the same as (q < p)p >= q is the same as NOT (p < q)
<p> means a paragraph of text. if you put an opening <p> all the following text will belong to this paragraph until you close it with </p>
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The question of whether the complexity class P is equal to the complexity class NP is one of the most important unsolved problems in computer science. It is not known if P is equal to NP, and this question is at the heart of the famous P vs. NP problem.
The question of whether the complexity class P equals the complexity class NP is one of the most important unsolved problems in computer science. It is not known if P is equal to NP or not. If P equals NP, it would mean that every problem for which a solution can be verified quickly can also be solved quickly. This would have significant implications for cryptography, optimization, and many other fields. However, as of now, it remains an open question.
"No Problem"Np means No problem.
NP=Nickel-Plate
NP = "Nurse Practitioner."
np means no pass, p means pass and i don't know what sp stand for.
No, the keyword "p" is not contained in the set of problems that can be solved in polynomial time, known as NP.
Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.
NP most commonly means nurse practitioner. It may also mean neuropsychiatric.
If you mean the interior plains of the USA, these would include Badlands NP and Theodore Roosevelt NP. If you include the interior plains of Canada, then add Elk Island NP, Grasslands NP, Riding Mountain NP; and perhaps Prince Albert NP and Wood Buffalo NP.
The binomial distribution can be approximated with a normal distribution when np > 5 and np(1-p) > 5 where p is the proportion (probability) of success of an event and n is the total number of independent trials.
If you mean the interior plains of the USA, these would include Badlands NP and Theodore Roosevelt NP. If you include the interior plains of Canada, then add Elk Island NP, Grasslands NP, Riding Mountain NP; and perhaps Prince Albert NP and Wood Buffalo NP.