Материал: [lect] Grubbs - Procedure for Detecting outlying observations in samples (1969)

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(Reference [3]).

DETECTINGOUTLYINGOBSERVATIONSIN SAMPLES

15

5.2 The critical values for T[ and T' for the 5% and 1% significance levels are due to David [3] and are given in Table 5. In Table 5 the subscript v = df indicates the total number of degrees of freedom associated with the independent estimate of standard deviation a and n indicates the number of observations

TABLE 5

Critical Values for T When Standard Deviation s, is Independent of Present Sample

 

 

 

T =

xn - X or X - xl

 

 

 

 

 

 

 

 

S,Si

 

 

 

 

 

n

3

4

5

6

7

8

9

10

12

v =

df

 

 

 

1% points

 

 

 

 

10

2.78

3.10

3.32

3.48

3.62

3.73

3.82

3.90

4.04

11

2.72

3.02

3.24

3.39

3.52

3.63

3.72

3.79

3.93

12

2.67

2.96

3.17

3.32

3.45

3.55

3.64

3.71

3.84

13

2.63

2.92

3.12

3.27

3.38

3.48

3.57

3.64

3.76

14

2.60

2.88

3.07

3.22

3.33

3.43

3.51

3.58

3.70

15

2.57

2.84

3.03

3.17

3.29

3.38

3.46

3.53

3.65

16

2.54

2.81

3.00

3.14

3.25

3.34

3.42

3.49

3.60

17

2.52

2.79

2.97

3.11

3.22

3.31

3.38

3.45

3.56

18

2.50

2.77

2.95

3.08

3.19

3.28

3.35

3.42

3.53

19

2.49

2.75

2.93

3.06

3.16

3.25

3.33

3.39

3.50

20

2.47

2.73

2.91

3.04

3.14

3.23

3.30

3.37

3.47

24

2.42

2.68

2.84

2.97

3.07

3.16

3.23

3.29

3.38

30

2.38

2.62

2.79

2.91

3.01

3.08

3.15

3.21

3.30

40

2.34

2.57

2.73

2.85

2.94

3.02

3.08

3.13

3.22

60

2.29

2.52

2.68

2.79

2.88

2.95

3.01

3.06

3.15

120

2.25

2.48

2.62

2.73

2.82

2.89

2.95

3.00

3.08

co

2.22

2.43

2.57

2.68

2.76

2.83

2.88

2.93

3.01

 

 

 

 

 

5% points

 

 

 

 

10

2.01

2.27

2.46

2.60

2.72

2.81

2.89

2.96

3.08

11

1.98

2.24

2.42

2.56

2.67

2.76

2.84

2.91

3.03

12

1.96

2.21

2.39

2.52

2.63

2.72

2.80

2.87

2.98

13

1.94

2.19

2.36

2.50

2.60

2.69

2.76

2.83

2.94

14

1.93

2.17

2.34

2.47

2.57

2.66

2.74

2.80

2.91

15

1.91

2.15

2.32

2.45

2.55

2.64

2.71

2.77

2.88

16

1.90

2.14

2.31

2.43

2.53

2.62

2.69

2.75

2.86

17

1.89

2.13

2.29

2.42

2.52

2.60

2.67

2.73

2.84

18

1.88

2.11

2.28

2.40

2.50

2.58

2.65

2.71

2.82

19

1.87

2.11

2.27

2.39

2.49

2.57

2.64

2.70

2.80

20

1.87

2.10

2.26

2.38

2.47

2.56

2.63

2.68

2.78

24

1.84

2.07

2.23

2.34

2.44

2.52

2.58

2.64

2.74

30

1.82

2.04

2.20

2.31

2.40

2.48

2.54

2.60

2.69

40

1.80

2.02

2.17

2.28

2.37

2.44

2.50

2.56

2.65

60

1.78

1.99

2.14

2.25

2.33

2.41

2.47

2.52

2.61

120

1.76

1.96

2.11

2.22

2.30

2.37

2.43

2.48

2.57

co

1.74

1.94

2.08

2.18

2.27

2.33

2.39

2.44

2.52

The above percentage points are reproduced from H. A. David, "Revised upper percentage

points of the extreme studentized deviate from the sample mean," Biometrika, Vol. 43 (1956), pp. 449-451.

16

FRANK E. GRUBBS

Standardization of Sodium Hydroxide Solutions as Determined by Plant Laboratories Standard Used: Potassium Acid Phthalate (P.A.P)

 

 

 

 

Deviation of Averagefrom

Laboratory

(P.A.P.-.096000) X 103

Sums

Averages

Grand Average

1

1.893

 

 

 

 

 

1.972

5.741

1.914

+

.043

 

1.876

2

2.046

 

 

 

 

 

1.851

 

 

 

 

 

1.949

5.846

1.949

+

.078

3

1.874

 

 

 

 

 

1.792

 

 

-

 

 

1.829

5.495

1.832

.039

4

1.861

 

 

 

 

 

1.998

5.842

1.947

+

.076

 

1.983

5

1.922

 

 

 

 

 

1.881

 

 

+

.013

 

1.850

5.653

1.884

6

2.082

 

 

 

 

 

1.958

 

 

+

.152

 

2.029

6.069

2.023

7

1.992

 

 

 

 

 

1.980

 

 

+

.142

 

2.066

6.038

2.013

8

2.050

 

 

 

 

 

2.181

6.134

2.045

+

.174

 

1.903

9

1.831

 

 

 

 

 

1.883

 

 

-

.015

 

1.855

5.569

1.856

10

.735

 

 

 

 

 

.722

 

.745

-1.126

 

.777

2.234

11

2.064

 

 

 

 

 

1.794

 

 

+

.045

 

1.891

5.749

1.916

12

2.475

 

 

 

 

 

2.403

 

2.327

+

.456

 

2.102

6.980

GrandSum

67.350

1.871

 

 

GrandAverage

 

 

 

DETECTINGOUTLYING OBSERVATIONS IN SAMPLES

17

in the sample under study. We illustrate with an example on interlaboratory testing.

5.3 Example 6-Interlaboratory Testing. In an analysis of interlaboratory test procedures, data representing normalities of sodium hydroxide solutions were determined by twelve different laboratories. In all the standardizations, a tenth normal sodium hydroxide solution was prepared by the Standard Methods Committee using carbon-dioxide-free distilled water, Potassium acid phthalate (P. A. P.), obtained from the National Bureau of Standards, was used as the test standard.

Test data by the twelve laboratories are given in the table below. The P. A. P. readings have been coded to simplify the calculations. The variances between the three readings within all laboratories were found to be homogeneous. A one-way classification in the analysis of variance was first analyzed to determine

if the variation in laboratory results (averages) was statistically significant. This variation was significant, so tests for outliers were then applied to isolate the particular laboratories whose results gave rise to the significant variation. We are indebted to Dr. Grant Wernimont of the Eastman Kodak Co. for the data on Standardization of Sodium Hydroxide Solutions.

 

 

Analysis of Variance

 

 

Sourceof

Degrees of

Sum of Squares

Mean Square

 

Variation

Freedomd.f.

SS

MS

F-ratio

Between Labs

11

4.70180

.4274

F = 48.61

Within Labs

24

.21103

.008793

(Highly

Significant)

TOTAL

35

4.91283

 

 

The above analysis of variance shows that the variation between laboratories

is highly significant. To test if this (very significant) variation is due to one

(or perhaps two) laboratories that obtained "outlying" results (i.e. perhaps showing non-standard technique), we can test the laboratory averages for outliers. From the analysis of variance, we have an estimate of the variance of

an individual reading as .008793, based on 24 degrees of freedom. The estimated

standard deviation of an individual measurement is \/.008793 =

.094 and the

estimated standard deviation of the average of three readings

is therefore

.094//3

= .054.

 

Since the estimate of within-laboratory variation is independent of any

difference between laboratories, we can

use the statistic

T[ of section 5.1 to

test for outliers. An examination of the

deviations of the

laboratory averages

from the grand average indicates that Laboratory 10 obtained an average reading much lower than the grand average, and that Laboratory 12 obtained a high average compared to the overall average. To first test if Laboratory 10 is an outlier, we compute

T'

1.871 -

.745

.054

=20.9

 

 

This value of T' is obviously significant at a very low level of probability

[3] as an example here since they
of variance omitting

18

FRANK E. GRUBBS

(P << .01. Refer to Table 5 with n = 12 and v = 24 d.f.). We conclude therefore that the test methods of Laboratory 10 should be investigated.

Excluding Laboratory 10, we compute a new grand average of 1.973 and test if the results of Laboratory 12 are outlying. We have

2.327

- 1.973

=

6.56

 

.054

 

 

 

and this value of T' is significant at P << .01 (Refer to Table 5 with n = 11 and v = 24 d.f.). We conclude that the procedures of Laboratory 12 should also

be investigated.

To verify that the remaining laboratories did indeed obtain homogeneous results, we might repeat the analysis Laboratories 10 and 12. This calculation gives

 

Analysis

of Variance

 

 

 

 

 

(omitting labs 10 and 12)

 

 

 

Source of Variation

d.f.

SS

MS

F-ratio

 

Between Labs

9

.13889

.01543

F = 2.36

=

2.40

Within Labs

20

.13107

.00655

F.05(9, 20)

 

 

 

 

F.01(9, 20)

=

3.45

TOTAL

29

.26996

 

 

 

 

For this analysis, the variation between labs is not significant at the 5% level and we conclude that all the laboratories except No. 10 and No. 12 exhibit

the same capability in testing procedure.

In conclusion, there should be a systematic investigation of test methods for Laboratories No. 10 and No. 12 to determine why their test precedures are

apparently different from the other ten laboratories.

(For the above example, procedures for ranking means after the initial analysis of variance test could, of course, have been used. For example, Duncan's Multiple Range Test, Scheffe's Test, Tukey's procedure, etc., could have been used. Also, the test of Halperin, Greenhouse and Cornfield [9] could have been

used. We have used David's tables seem tailor-made for one or two specific laboratories.)

6. RECOMMENDEDCRITERIAFORKNOWN

STANDARDDEVIATION

6.1 Frequently the population standard deviation a may be known accurately. In such cases, Table 6 may be used for single outliers and we illustrate with the

following example.

6.2 Example 7 (a known). Passage of the Echo I (Balloon) Satellite was recorded on star-plates when it was visible. Photographs were made by means

of a camera with shutter automatically timed to obtain a series of points for

the Echo path. Since the stars were also photographed at the same times as the Satellite, all the pictures show star-trails and so are called "star-plates."

DETECTINGOUTLYINGOBSERVATIONSIN SAMPLES

19

 

 

TABLE 6

 

 

 

Critical Values of TI.

and T0t

When the Population

Standard Deviation a is Known

Number of

 

5%

1%

0.5%

 

Observations

Significance

Significance

Significance

 

n

 

Level

Level

Level

 

2

 

1.39

1.82

1.99

 

3

 

1.74

2.22

2.40

 

4

 

1.94

2.43

2.62

 

5

 

2.08

2.57

2.76

 

6

 

2.18

2.68

2.87

 

7

 

2.27

2.76

2.95

 

8

 

2.33

2.83

3.02

 

9

 

2.39

2.88

3.07

 

10

 

2.44

2.93

3.12

 

11

 

2.48

2.97

3.16

 

12

 

2.52

3.01

3.20

 

13

 

2.56

3.04

3.23

 

14

 

2.59

3.07

3.26

 

15

 

2.62

3.10

3.29

 

16

 

2.64

3.12

3.31

 

17

 

2.67

3.15

3.33

 

18

 

2.69

3.17

3.36

 

19

 

2.71

3.19

3.38

 

20

 

2.73

3.21

3.39

 

21

 

2.75

3.22

3.41

 

22

 

2.77

3.24

3.42

 

23

 

2.78

3.26

3.44

 

24

 

2.80

3.27

3.45

 

25

 

2.81

3.28

3.46

 

Xi < X2 < X3 < '*

< Xn

T

= (X -X,)/

T/

= (xn -

I)/a

This table is taken from the paper of Grubbs, Reference [8].

The x- and y-coordinate of each point on the Echo path are read from a photograph, using a stereo-comparator. To eliminate bias of the reader, the

photograph is placed in one position and the coordinates are read; then the photograph is rotated 180? and the coordinates reread. The average of the two

readings is taken as the final reading. Before any further calculations are made, the readings must be "screened" for gross reading or tabulation errors. This is done by examining the difference in the readings taken at the two positions of the photograph.

Recorded below are a sample of six readings made at the two positions and the differences in these readings. On the third reading, the differences are rather

large. Has the operator made an error in positioning the cross-hair on the point? For this example, an independent estimate of aois available since extensive tests on the stero-comparator have shown that the standard deviation in reader's error is about 4 microns. The determination of this standard error was based on such a large sample that we can assume a = 4 microns. The standard

deviation of the difference in two readings is therefore /42 + 42 =

32

or 5.7 microns.

 

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