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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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Question

Q3. Using Data set 2 about the process times taken for the last xxxxx parts (from data part n1 to part n2). - n1= 27.6. n2=97.6 - Draw a histogram of your data and comment on if it looks like to be close to Normal distribution - Assume it follows normal distribution, calculate its parameters and draw Quantile-Quantile plot and comment about the plot. - Draw scatter diagram (XY plot in excel) between two successive data (X axis is Xi is, Y axis is Xi+1) and comment about the dependency of successive data points. - Calculate the correlation between two successive data (Xi is one column, Xi+1 is the other column of data) and comment about the dependency of successive data points. (You can use the correlation function of excel, or formulae given our classes.) - Apply Chi-square test to check the goodness-of-fit using the significance level = 0.05. What is the p-value of your test? (You will need to use Norm.inv function of excel to answer this question)

Data set 2
Part No
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Process times
(min)
3.64
4.68
3.64
3.12
4.16
3.12
3.64
5.2
4.16
4.16
4.68
4.68
5.2
3.64
4.16
3.64
4.68
2.6
3.12
3.12
5.2
4.68
5.2
2.6
3.12
4.68
5.2
4.68
3.64
3.64
5.2
2.6
3.12
3.64
4.16
2.6
4.68
4.68
4.68
3.12
5.2
4.16
3.12
5.2
3.12
3.12
5.2
5.2
3.64
5.2
Part No
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
Process
times (min)
2.6
4.68
4.16
3.64
3.64
5.2
4.68
3.64
4.16
3.64
4.68
4.68
4.16
4.16
5.2
3.64
2.6
5.2
3.12
3.12
2.6
4.68
3.64
5.2
2.6
3.64
3.64
4.68
5.2
4.68
3.64
2.6
5.2
3.64
3.12
3.64
3.64
3.12
4.68
5.2
4.16
2.6
4.68
4.68
4.68
4.16
5.2
3.64
4.68
5.2

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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