Use Chauvenet's criterion to identify any outliers in the data which should be rejected. Don't use the chauvenets table. Use the normal distribution table.
Use Chauvenet's criterion to identify any outliers in the data which should be rejected. Don't use the chauvenets table. Use the normal distribution table.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
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5
6
6 temperature measurements are made in a laboratory over a period of time and the following
values are obtained:
31.4,31.6,31.2,31.5,32.5,32.8
Use Chauvenet's criterion to identify any outliers in the data which should be rejected. Don't use the
chauvenets table. Use the normal distribution table.
es/standard-normal-table
Z
0.0
0.1
0.2
0.3
0.4
F
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.3
24
2.5
B
2.6
2.7
Kar
2.8
2.9
3,0
3.1
F
3.3
3.4
3.5
3.6
3.7
3.8
0.00
0.01
0.0000 0.0040
0.0398 0.04
0.0438
0.0793
0.11 0.0832
0.0478 0.0517 0.0557 0.0596 0.0636 0.0675 0.0714
0.0871 0.0910 0.094
0.0753
0.1255 0.1103 0.1141
0.1554 0.1591 0.1628 0.362 0.1331 0.1368 0.1406 0.1443 0.1480 0.1517
0.1915 0.1950 0.1985 0.2019 0.1700 0.1736 0.1772 0.1808
0.2257 0.2291 0.2324 0.22 0.2054 0.2088 0.2123 0.21570-1844 0.1879
0.2580 0.2611 0.2642 0.2357 0.2389 0.2422 0.2454 0.24 0.7190 0.2224
0.2881 0.291002642 0.2673 0.2704 0.2734 0.27540.2486 0.2517 0.2549
0.3159 0.31860.299 0.2967 0.2995 0.302303064027940.2823 0.2852
0.3413 0.300.3212 0.3238 0.3264 0.3282 0.05 0.3078 0.3106 0.3133
0.3438 0.3461 0.3485 0.3508 0.35310333503340 0.3365 0.3389
0.36430.3665 0.3686 0.3708 0.3729 0.3749 03724 0.3577 0.3599 0.3621
0.3849 0.3869 0.3888 0.3907 0.3925 0.3242 0.3770 0.3790 0.3810 0.3830
0.4032 0.4049 0.4066 0.408210.400 104 0.3962 0.39800.9997 0.4015
0.4192 0.4207 0.4222 0.4236 0.4251 0.4265
0.4115 0.4131 0.4147 0.4162 0.4177
0.4332 0.4345 0.4357 0.4370 0415304265 0.47279 04792 0.4306 0.4319
0.4452 0.4463 0.4474
0.4554 0.4564 0.4573
0.4641 0.4649 0.4656 0.4664 0
0.4434 0.4495 0.4394 0.4406 0.4418 0.4429 0.4441
0.4582040504505
0.4515 0.4525 0.4535 0.4545
04591 0.459
0.4608 0.4616 0.4635 0.4633
0.4671
0.4713 0.4719 0.4726 0.4732 467 0.4678 0.46
0.4686 0.4693 0.4699 0.4706
20.4738 0.4744 0.4750 0.4756 0.4761 0.4767
0.4798 0.4803 0.4808 0.4812 0.4817
0.4772 0.4778 0.4783
0.4793
04788
0.4821 0.4826 0.4830 0.48M
0.4868 0.4871048
Deine
0.4898 0.4901
0.4901 0.4904
0.4861 0.4864
10 4506
0.4893
Besser
posses
0.4842 0.4846 0.4850 0.4854 0.4857
0.4878 0.4881 0.4684 0.4887 0.4890
0.4906 0.4909 0.49110.400.48⁹0
04931 1049
0.4934
0.4922 0.4925
04015
10.4925
0.4948 0.49499495104952
9.4937
493 6.4896
ANDDO
0.4918 0.4920
0.4927 0.4929
0:4938 0.4940 0.4541 045941 CAME
0.4545 0.4946
0404955 0.4956
0.4959 0.4960 0.49610.49520493 10.490
00.4966 0.4967 0.4968
0.4969
0.4970 0.4971 0.4972 04973 0.4974
0.4977 0.4977
0.4978 0.4979 0.4979 0.4960 0.4981
0.49810.49820.4982 0.4983 0.4984 0.4984 0.4985 0.4985 0.4956 0.4986
0.4990 0.499 0467049680.4988 0.4989 0.4989 0.4989 0.4990 0.4990
0.4993 0.499310400410 0.4992 0.4992 0.4992 0.4992 0.4993 0.4993
0.4995 0.4995 040 104000 104994 0.4994 0.4995 0.4995 0.4995
0.4997 6.4997 0.4997 0am toam 10400 104996 0.4996 0.499604997
0.4997 0.4997
0.4998 0.4998 0.4998 0.4996 0.49969.49000097 0.4997 0.4998
0.4998 0.4998 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999
0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 04999
0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999
0.4994
0.4996 0.4990 0.4990
0.4998
04974
0.08
0.0080 0.0120 0.0160 0.0199 0.0239 0.0279 0.0319
0.02 0.03 0.04 0.05 0.06 0.07
7
4
ten
n
4932
0.4916
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