The probability distribution of the random variable X represents the number of hits a baseball player obtained in a gar the 2012 baseball season. 1 2 4 5 P(x) 0.1668|0.3412 0.2912 0.1495 0.0384 | 0.0129 The probability distribution was used along with statistical software to simulate 25 repetitions of the experiment (25 ga The number of hits was recorded. Approximate the mean and standard deviation of the random variable X based on t simulation. The simulation was repeated by performing 50 repetitions of the experiment. Approximate the mean and standard deviation of the random variable. Compare your results to the theoretical mean and standard deviation. Wha property is being illustrated? Click the icon to view the data tables
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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