We want to investigate the correlation between concentration of Se (Selenium) in the teeth and its concentration in the liver in 20 Beluga Whales. 240 220 We suspect that the higher the concentration in the liver, the higher the concentration in the teeth. A plot of the data is given at right, and the following summary statistics are given for these data: 200 180 160 x = 20.68 Sx = 13.45 y = 156.60 Sy = 36.06 140 r = 0.54 Se = 31.25 120 Before actually computing its value (that is, by just looking at the scatterplot), how do we know that r > 0 (rather than r = 0 or r< 0)? 10 20 30 40 Liver Se (ug/g dry wt) Tooth Se (ng/g dry wt)
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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