The lower bound of 3.0 is 3.0
The upper bound of a number is the smallest whole number that is greater than or equal to the given number. In this case, the upper bound of 6800 is 6800 itself. The lower bound of a number is the largest whole number that is less than or equal to the given number. Therefore, the lower bound of 6800 is also 6800.
If the range is the real numbers, it has a lower bound (zero) but no upper bound.
The answer depends on the level of accuracy of the value 0.
no won noes * * * * * It means that there is an upper and lower bound or limit. There is the lower bound such that you exclude any smaller numbers, and an upper bound such that you exclude bigger numbers. What you do wit hnumbers that are equal to the bounds depends on the nature of the bounds.
· whether it is linear, quadratic or exponential · whether it has an upper or lower bound · whether it has a minimum or a maximum value · whether it is constant, decreasing or increasing
Lower bound is 17.6 and upper bound is 17.8
The lower bound of 3.0 is 3.0
The answer is B.
You cannot list them: unless the inequality is trivial, since there are infinitely many real numbers in any range. You need toidentify the lower bound;determine whether or not the lower bound is included (
What is the lower and upper bound of 9.3 in 1 s.f.?
The lower bound is 16.35
The upper bound of a number is the smallest whole number that is greater than or equal to the given number. In this case, the upper bound of 6800 is 6800 itself. The lower bound of a number is the largest whole number that is less than or equal to the given number. Therefore, the lower bound of 6800 is also 6800.
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Do you mean, "the difference between an algorithm that runs in polynomial time, and one that runs in exponential time".First a real quick review. A polynomial is any equation of the formy = cmxm + ... + c2x2 + c1x + c0 ,where ci are constantsAn exponential function is something of the formy = cxThese functions grow much faster than any polynomial function.So, if T(n) describes the runtime of an algorithm as a function of whatever (# of inputs, size of input, etc.)., and T(n) can be bound above by any polynomic function, then we say that algorithm runs in polynomial time.If it can't be bound above by a polynomial function, but can be bound above by an exponential function, we say it runs in exponential time.Note how ugly an exponential algorithm is. By adding one more input, we roughly double (or triple, whatever c is) the run-time.
The lower bound is 0.5 less and the upper bound is 0.5 more.
4.5