Suppose two distributions with the following characteristics are given. Distribution A H= 47,100 6= 6,436 Distribution B H= 31.80 O = 4.22 If a value from distribution A is 57,900 and a value from distribution B is 34.0, convert each value to a standardized z-value and indicate which one is relatively closer t its respective mean. Choose the correct answer below. O A. The value from distribution A is relatively closer to its mean because its corresponding z-value is larger than the z-value corresponding to the value from distribution B. O B. The value from distribution B is relatively closer to its mean because its corresponding z-value is smaller than the z-value corresponding to the value from distribution A. O c. The value from distribution A is relatively closer to its mean because its corresponding z-value is smaller than the z-value corresponding to the value from distribution B. O D. The value from distribution B is relatively closer to its mean because its corresponding z-value is larger than the z-value corresponding to the value from distribution A.
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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