The following data represent the energy consumption of coal (in billions of Btu) by each of the 50 states and the District of Columbia. 613 723 267 60 372 15 19 92 306 38 413 8 736 156 478 365 264 1015 329 679 1498 52 1365 142 423 350 445 776 1267 0 26 356 173 373 335 34 937 250 33 84 253 84 1224 743 582 2 33 426 474 Use the data to construct i. A frequency distribution and a relative frequency distribution with 7 classes.
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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