12Use the table below to find the percentage of data items in a normal distribution the lie between z= 1.1 and z= 2.7.(Picture of the chart uploaded )The percentage of data items in a normal distribution that lie between z=1.1 and z=2.7 is ____% Z-SCore0.10.20.30.40.50.60.70.80.91.0Percentile 53.98 57.93 61.79 65.54 69.15 72.57 75.80|78.81 81.59 84.131.41.11.21.31.61.5Percentile 86.43 88.49 90.32 91.92 93.32 94.52 95.54 96.41 97.1397.722.4Z-Score1.71.81.92.02.12.22.32.72.92.5Percentile 9821 98.61 98.93 99 18 99.38 99.53 99 65 99.74 99.81 99 87Z-Score2.62.83.0

The given table is, From the table, the percentage corresponding to z-score = 1.1 is,…

Answered: 12 Use the table below to find the…

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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12 Use the table below to find the percentage of data items in a normal distribution the lie between z= 1.1 and z= 2.7. (Picture of the chart uploaded ) The percentage of data items in a normal distribution that lie between z=1.1 and z=2.7 is ____%

Z-SCore
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Percentile 53.98 57.93 61.79 65.54 69.15 72.57 75.80|78.81 81.59 84.13
1.4
1.1
1.2
1.3
1.6
1.5
Percentile 86.43 88.49 90.32 91.92 93.32 94.52 95.54 96.41 97.1397.72
2.4
Z-Score
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.7
2.9
2.5
Percentile 9821 98.61 98.93 99 18 99.38 99.53 99 65 99.74 99.81 99 87
Z-Score
2.6
2.8
3.0

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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