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In statistics, a moving average (rolling average or running average or moving mean or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set.
Therefore, a naïve algorithm to calculate the estimated variance is given by the following: Let n ← 0, Sum ← 0, SumSq ← 0. For each datum x : n ← n + 1. Sum ← Sum + x. SumSq ← SumSq + x × x. Var = (SumSq − (Sum × Sum) / n) / (n − 1) This algorithm can easily be adapted to compute the variance of a finite population: simply ...
In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to ...
Amortized analysis. In computer science, amortized analysis is a method for analyzing a given algorithm's complexity, or how much of a resource, especially time or memory, it takes to execute. The motivation for amortized analysis is that looking at the worst-case run time can be too pessimistic.
This intuition is captured in the following formula for average polynomial running time, which balances the polynomial trade-off between running time and fraction of inputs: Pr x ∈ R D n [ t A ( x ) ≥ t ] ≤ p ( n ) t ϵ {\displaystyle \Pr _{x\in _{R}D_{n}}\left[t_{A}(x)\geq t\right]\leq {\frac {p(n)}{t^{\epsilon }}}}
In computer science, best, worst, and average cases of a given algorithm express what the resource usage is at least, at most and on average, respectively. Usually the resource being considered is running time, i.e. time complexity, but could also be memory or some other resource. Best case is the function which performs the minimum number of ...
Median of medians. In computer science, the median of medians is an approximate median selection algorithm, frequently used to supply a good pivot for an exact selection algorithm, most commonly quickselect, that selects the k th smallest element of an initially unsorted array. Median of medians finds an approximate median in linear time.
The simplicity of this approach is that the time taken can be easily adjusted for an individual's own (chosen) speed on the flat; at 8 km/h (flat speed) the route will take 4 hours and 6 minutes. The rule has been tested on fell running times and found to be reliable. Scarf proposed this equivalence in 1998.
The average number of steps taken by the Euclidean algorithm has been defined in three different ways. The first definition is the average time T ( a ) required to calculate the GCD of a given number a and a smaller natural number b chosen with equal probability from the integers 0 to a − 1 [95]
Determine the effective CPI, MIPS (Millions of instructions per second) rate, and execution time for this program. CPI = 45000 × 1 + 32000 × 2 + 15000 × 2 + 8000 × 2 100000 = 155000 100000 = 1.55 {\displaystyle {\text{CPI}}={\frac {45000\times 1+32000\times 2+15000\times 2+8000\times 2}{100000}}={\frac {155000}{100000}}=1.55}