74.9 45.1 132.1 104.7 33 324 7 59.9 87.5 56.0 154.2 85.5 75 A USE SALT
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!
![63.2
36.3
26.2
53.2
65.3 32.0 65.0
66.3
68.9
35.2
25.1
32.5 54.0 42.4
77.5 123.2
66.3
92.7
56.9 77.1 27.5
69.2
73.8
71.5
58.5
67.2 78.6 33.2
74.9
45.1 132.1 104.7
63.2 59.6 75.7
39.2 69.9
84.7 24.2
87.5
56.0 154.2 85.5 77.5
37.5
41.1
A USE SALT
(a) Use a calculator with mean and sample standard deviation keys to find the sample mean x and sample standard deviation s. (Round your answers bto four decimal places.)
x = 64.1000
s 27.0625
v crimes per 1000 people
v crimes per 1000 people
(b) Let us say the preceding data are representative of the population crime rates in Denver neighborhoods. Compute an 80% confidence interval for a, the population mean crime rate for all Denver neighborhoods. (Round your answers to one decimal place.)
58.0
x crimes per 1000 people
]x crimes per 1000 people
lower limit
upper limit
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