In a study, a large sample was used to estimate the mean systolic blood pressures in a population, and was found to follow a normal distribution (bell-shaped curve). In this study, the systolic blood pressure for men and women grouped together had a mean of 120.1 mmHg with a standard deviation of 15.1 mmHg. Using the empirical rule, what percentage of the population would you estimate to be between 150.3 and 165.4 mmHg? Give your answer as a percentage rounded to one decimal place and don't include units (don't write mmHg or a percent sign).
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!
In a study, a large sample was used to estimate the mean systolic blood pressures in a population, and was found to follow a
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