(a) Find the value of x, the percentage of linen treads between the breaking strength of 25.0-30.0 oz.(b) Construct a frequency distribution table that includes the (exclusive) class limits, classmidpoint (m), frequency (f), mf and m2f.(c) Determine the mean, variance and standard deviation of breaking strength of linentreads. The following data represent a sample of breaking strength of linen threads (in oz) and itspercentage, selected from a small factory. A total of 200 linen treads were selected forobservation in this study.Table Q1: Breaking strength (in oz) linen treads and its percentageBreaking StrengthPercentage (%) ofLinen Tread15.0 – 20.020.0 – 25.01225.0 – 30.030.0 - 35.02735.0 – 40.02140.0 – 45.01145.0 – 50.07

Data is given for linen tread We have to calculate, value of x Mean, variance and standard…

Answered: Find the value of x, the percentage of…

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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(a) Find the value of x, the percentage of linen treads between the breaking strength of 25.0-
30.0 oz.

(b) Construct a frequency distribution table that includes the (exclusive) class limits, class
midpoint (m), frequency (f), mf and m2f.

The following data represent a sample of breaking strength of linen threads (in oz) and its
percentage, selected from a small factory. A total of 200 linen treads were selected for
observation in this study.
Table Q1: Breaking strength (in oz) linen treads and its percentage
Breaking Strength
Percentage (%) of
Linen Tread
15.0 – 20.0
20.0 – 25.0
12
25.0 – 30.0
30.0 - 35.0
27
35.0 – 40.0
21
40.0 – 45.0
11
45.0 – 50.0
7

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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