Test Bank For Probability and Statistics for Computer Scientists Third Edition

Test Bank For Probability and Statistics for Computer Scientists Third Edition

This course is about uncertainty, measuring and quantifying uncertainty, and making decisions under uncertainty. Loosely speaking, by uncertainty we mean the condition when
results, outcomes, the nearest and remote future are not completely determined; their development depends on a number of factors and just on a pure chance.
Simple examples of uncertainty appear when you buy a lottery ticket, turn a wheel of
fortune, or toss a coin to make a choice.
Uncertainly appears in virtually all areas of Computer Science and Software Engineering.
Installation of software requires uncertain time and often uncertain disk space. A newly
released software contains an uncertain number of defects. When a computer program is
executed, the amount of required memory may be uncertain. When a job is sent to a printer,
it takes uncertain time to print, and there is always a different number of jobs in a queue
ahead of it. Electronic components fail at uncertain times, and the order of their failures
cannot be predicted exactly. Viruses attack a system at unpredictable times and affect an
unpredictable number of files and directories.
Uncertainty surrounds us in everyday life, at home, at work, in business, and in leisure. To
take a snapshot, let us listen to the evening news.
Example 1.1 . We may find out that the stock market had several ups and downs today
which were caused by new contracts being made, financial reports being released, and other
events of this sort. Many turns of stock prices remained unexplained. Clearly, nobody would
have ever lost a cent in stock trading had the market contained no uncertainty.
We may find out that a launch of a space shuttle was postponed because of weather conditions. Why did not they know it in advance, when the event was scheduled? Forecasting
weather precisely, with no error, is not a solvable problem, again, due to uncertainty.
To support these words, a meteorologist predicts, say, a 60% chance of rain. Why cannot
she let us know exactly whether it will rain or not, so we’ll know whether or not to take
our umbrellas? Yes, because of uncertainty. Because she cannot always know the situation
with future precipitation for sure.
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2 Probability and Statistics for Computer Scientists
We may find out that eruption of an active volcano has suddenly started, and it is not clear
which regions will have to evacuate.
We may find out that a heavily favored home team unexpectedly lost to an outsider, and
a young tennis player won against expectations. Existence and popularity of totalizators,
where participants place bets on sports results, show that uncertainty enters sports, results
of each game, and even the final standing.
We may also hear reports of traffic accidents, crimes, and convictions. Of course, if that
driver knew about the coming accident ahead of time, he would have stayed home. ♦
Certainly, this list can be continued (at least one thing is certain!). Even when you drive
to your college tomorrow, you will see an unpredictable number of green lights when you
approach them, you will find an uncertain number of vacant parking slots, you will reach
the classroom at an uncertain time, and you cannot be certain now about the number of
classmates you will find in the classroom when you enter it.
Realizing that many important phenomena around us bear uncertainty, we have to understand it and deal with it. Most of the time, we are forced to make decisions under
uncertainty. For example, we have to deal with internet and e-mail knowing that we may
not be protected against all kinds of viruses. New software has to be released even if its
testing probably did not reveal all the defects. Some memory or disk quota has to be allocated for each customer by servers, internet service providers, etc., without knowing exactly
what portion of users will be satisfied with these limitations. And so on.
This book is about measuring and dealing with uncertainty and randomness. Through basic
theory and numerous examples, it teaches
– how to evaluate probabilities, or chances of different results (when the exact result is
uncertain),
– how to select a suitable model for a phenomenon containing uncertainty and use it in
subsequent decision making,
– how to evaluate performance characteristics and other important parameters for new
devices and servers,
– how to make optimal decisions under uncertainty.
Summary and conclusion
Uncertainty is a condition when the situation cannot be predetermined or predicted for
sure with no error. Uncertainty exists in computer science, software engineering, in many
aspects of science, business, and our everyday life. It is an objective reality, and one has to
be able to deal with it. We are forced to make decisions under uncertainty.

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