The mean yearly rainfall in Sydney, Australia, is about 137 mm and the standard deviation is about 69 mm. Assume yearly rainfall is normally distributed. The mean yearly rainfall in Sydney, Australia, is about 137 mm and the standard deviation is about 69 mm.Assume yearly rainfall is normally distributed.Round the probabilities to four decimal places.It is possible with rounding for a probability to be 0.0000.a) State the random variable.Select an answerb) Find the probability that a randomly selected year of rain in Sydney, Australia has a yearly rainfall of-43.4 mm or more.c) Find the probability that a randomly selected year of rain in Sydney, Australia has a yearly rainfall of145.4 mm or less.d) Find the probability that a randomly selected year of rain in Sydney, Australia has a yearly rainfallbetween -43.4 and 145.4 mm.e) Find the probability that a randomly selected year of rain in Sydney, Australia has a yearly rainfall that isat most 33.5 mm. f) Is a yearly rainfall of 33.5 mm unusually low for a randomly selected year of rain in Sydney, Australia?Why or why not?Select an answerg) What yearly rainfall do 46% of all years of rain in Sydney, Australia have more than?Round your answer to two decimal places in the first box.Put the correct units in the second box.

Mean Standard deviation Yearly rainfall is normally distributed.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The mean yearly rainfall in Sydney, Australia, is about 137 mm and the standard deviation is about 69 mm. Assume yearly rainfall is normally distributed.

f) Is a yearly rainfall of 33.5 mm unusually low for a randomly selected year of rain in Sydney, Australia?
Why or why not?
Select an answer
g) What yearly rainfall do 46% of all years of rain in Sydney, Australia have more than?
Round your answer to two decimal places in the first box.
Put the correct units in the second box.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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