By David J. Lilja
Measuring computing device functionality units out the elemental concepts utilized in examining and realizing the functionality of desktops. The emphasis is on sensible tools of size, simulation, and analytical modeling. David Lilja discusses functionality metrics and gives special assurance of the concepts utilized in benchmark courses. as well as intuitive motives of key statistical instruments, he describes the final "design of experiments" method and exhibits how the utmost quantity of knowledge will be received with minimal attempt. good points contain appendices directory universal likelihood distributions and statistical tables and a word list of significant technical phrases.
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These errors affect the accuracy of the measurements. It is up to the skill of the experimenter to control and eliminate systematic errors. Random errors, on the other hand, are completely unpredictable, nondeterministic, and need not be controllable. They are also unbiased in that a random error has an equal probability of either increasing or decreasing a measurement. Random errors may be the result of the measuring tool, the observer reading the output of the tool, or the random processes within the system being studied.
2 Determining the number of measurements needed We can see from the confidence-interval formula that the size of the interval is inversely dependent on the square root of the number of measurements that we make. Since we typically would like to minimize the number of measurements, we can use this formula to determine how many measurements are necessary to produce a confidence interval of a specified width. Suppose that we wish to determine a confidence interval for actual value x is within the interval so that there is a probability of 1 − α that the .
Let b1, b2, …, bn be the set of n before measurements and a1, a2, …, an be the set of corresponding after measurements. Then we simply need to find a confidence interval for the n difference values, d1 = a1 − b1, d2, = a2 − b2, …, dn = an − bn. 1, the confidence interval (c1, c2) for the mean of the differences when n ≥ 30 is given by where is the arithmetic mean of the di values and sd is the corresponding standard deviation. As before, if the number of measurements is less than 30, the z1−α/2 value should be replaced by the t1−α/2; n−1 value, which is a t distribution with n − 1 degrees of freedom.
Measuring Computer Performance by David J. Lilja