Suppose the systolic blood pressure (in mm) of adult males has an approximately normal distribution with mean μ =125 and standard deviation σ =14. Create an empirical rule graph with the following: A title and label for the horizontal axis including units. Vertical lines for the mean and first 3 standard deviations in each direction with numerical labels on the horizontal axis Labels for the areas of the 8 regions separated by the vertical lines as well.
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!
Suppose the systolic blood pressure (in mm) of adult males has an approximately
Create an
- A title and label for the horizontal axis including units.
- Vertical lines for the mean and first 3 standard deviations in each direction with numerical labels on the horizontal axis
- Labels for the areas of the 8 regions separated by the vertical lines as well.
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