Section 2.2 (81) In the early stages of the deadly SARS (severe acute respiratory syndrome) epidemic in 2003, the number of cases was increasing by about 18% each day. On March 17, 2003 (the first day for which statistics were reported by the World Health Organization), there were 167 cases. Find an exponential model that predicts the number of cases "t" days after March 17, 2003, and use it to estimate the number of cases on March 31, 2003. (The actual reported number of cases was .)
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!
Section 2.2 (81)
In the early stages of the deadly SARS (severe acute respiratory syndrome) epidemic in 2003, the number of cases was increasing by about 18% each day. On March 17, 2003 (the first day for which statistics were reported by the World Health Organization), there were 167 cases. Find an exponential model that predicts the number of cases "t" days after March 17, 2003, and use it to estimate the number of cases on March 31, 2003. (The actual reported number of cases was .)
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