Suppose you draw an observation (x = 91) from non-std normal distribution, X~N(109,14). We can convert x from this non-standard normal distribution to a standard normal distribution Z~N(0,1). If we do this, then our observation becomes z = ______. (Round your answer to two decimal places, ex: 0.12)

Suppose you draw an observation (x = 91) from non-std normal distribution, X~N(109,14). We can convert x from this non-standard normal distribution to a standard normal distribution Z~N(0,1). If we do this, then our observation becomes z = ______. (Round your answer to two decimal places, ex: 0.12)

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter13: Probability And Calculus

Section13.3: Special Probability Density Functions

Problem 8E

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Suppose you draw an observation (x = 91) from non-std normal distribution, X~N(109,14). We can convert x from this non-standard normal distribution to a standard normal distribution Z~N(0,1). If we do this, then our observation becomes z = ______.
(Round your answer to two decimal places, ex: 0.12)

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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