Using a unit normal tableMean = 100Standard deviation = 32 2ΔΔΔThe minimum z-score necessary to be in the highest 5% of the low-density lipoprotein distribution is z =X =Use this z-score to determine X, the corresponding low-density lipoprotein level.This score, X, is theO 16.86%12.45%14.07%O 1.14%Low-density lipoprotein levels between 130 and 159 are considered to be borderline high. What percentage of people have LDLS in this range?50%What percentage of people have the optimal level of LDLs (a level below 100)?40%O 20%31.14%E0$4percentile of low-density lipoprotein levels among people. The percentile rank of this score isR%5T61&728UZGrade It NowSave & ContinuContinue without sa0K

For the distribution of the raw values, it is given that, The mean, μ=100. The standard deviation,…

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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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Using a unit normal table Mean = 100 Standard deviation = 32

2
ΔΔΔ
The minimum z-score necessary to be in the highest 5% of the low-density lipoprotein distribution is z =
X =
Use this z-score to determine X, the corresponding low-density lipoprotein level.
This score, X, is the
O 16.86%
12.45%
14.07%
O 1.14%
Low-density lipoprotein levels between 130 and 159 are considered to be borderline high. What percentage of people have LDLS in this range?
50%
What percentage of people have the optimal level of LDLs (a level below 100)?
40%
O 20%
3
1.14%
E
0
$
4
percentile of low-density lipoprotein levels among people. The percentile rank of this score is
R
%
5
T
6
1
&
7
2
8
U
Z
Grade It Now
Save & Continu
Continue without sa
0
K

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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