The table below gives the number of suicides estimated in the U.S. for a recent year by age, race (black or white), and sex. We are interested in possible relationships between age, race, and sex. We will let suicide victims be our population. Race and Sex 1-14 15-24 25-64 over 64 TOTALS 210 3,355 13,615 white, male 22,050 white, female 75 black, male 580 5 3,385 4,930 465 1,670 330 1,055 black, female o all others 40 270 TOTALS 310 4,650 18,780 29,760 O Part (a) Fill in the column for the suicides for individuals over age 64 and fill in the row for all other races. Race and Sex 1-14 15-24 | 25-64 over 64 TOTALS 210 v 22,050 white, male white, female 75 3,355 13,615 4870 580 3,385 890 v 4,930 v 1,670 v 330 black, male 5 465 1,055 145 black, female o 40 270 20 all others 20 210 455 95 780 TOTALS 310 4,650 18,780 6020 29,760 O Part (b) O Part (c) O Part (d) Find the probability that a randomly selected individual was black. (Enter your probability as a fraction.) O Part (e) Find the probability that a randomly selected individual was male. Do not include "all others" as male individuals. (Enter your probability as a fraction.) O Part () Out of the individuals over age 64, find the probability that a randomly selected individual was a black or white male. Do not include "all others" as black or white male individuals. (Enter your probability as a fraction.)

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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!