A random sample of 90 observations produced a mean of ?⎯⎯⎯=26.3 from a population with a normal distribution and a standard deviation ?=2.08.
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!
A random sample of 90 observations produced a mean of ?⎯⎯⎯=26.3 from a population with a
The given data:
Mean,
Standard deviation,
Sample of observation,
(a) 90% confidence interval for is given as:
z score of is given as:
The confidence interval is given as:
Substitute the values into the above equation.
Therefore, the 90% confidence interval is (25.94, 26.661)
(b) 99% confidence interval for is given as:
z score of is given as:
The confidence interval is given as:
Substitute the values into the above equation.
Therefore, the 99% confidence interval is ( 25.735, 26.865)
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