1011,
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TABLE OF CONTENTS	
	Page
Overview	
I. Statistical Analysis of the Machine Experimental Data . . . . .	. .
Forward-Bakcward State Transition Analysis . . . . . . . .. . .	. .
Experim.ental.Data Randomness Analysis . . . . . . . . . . .	4
Best Strategy . . . # . . . . . . . ... . . . . . . . . . . . .	.. 15
II. Analysis of S2 Data Responses . . . . . . . . # .	. . 16
Strategy of S2 . . . . . . . . . . . . . . . . . . . . . . . .	. . 16
Total Color Choices . . . . . . . . . . . . . . . . . . .	. . 16
State Transition Color Choice . . . . . . . . . . . . . .	. .. 19
Hit Analysis . . . ... . . . . . . . I . . . . . . . . . . . . .	. . 21
Learning from Trial to Trial . . . . . . . . . . . . . . .	. . 21
Learning Within a Trial . . . . . . . . . . . . . . . . .	. . 20
III. miscellaneous . . . . . . . . . . . . . . . . . . . . . . . . .	. . 30
General Trial Information . . . . . . . . . . . . . . . . . . .	. . 31
Machine States . . . . . . . . . . . . . . . . . . . . . . . .	. . 31
Plots of Passes . . . . . . . . . I . . . . . . . . . ... . . .	. . 31
Subject - Future Machine State Transition . . . . . . . . . . .	. . 40
Distribution of Machine State Colors for Machine 2 . . . . . .	. . 41
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Page
			
Figure	1 a	Distribution of Machine Yellows Over Trials	6
	l.l.b	Distribution of Machine Greens Over Trials	7
		Distribution of Blues Over Trials	8
	lJ.d	Distribution of Machine Reds Over Trials	9
Figure	1.2	Distribution of Machine Colors When Samples are	
		Taken Five at a Time	
10
Figure	1.3	Distribution of Machine Colors When Samples are	
		Taken 100 at a Time	
Figure	1.4	Distri bution of Machine Reds When the Samples	
		are Taken 100 at a Time	12
Figure	1.5	Machine Color Distribution for Machine 1 and	
		Machine 2 on a Trial to Trial.Basis	14
Figure	2.1	S2 Col or'Choices	17
Figure	2.2	Plot of Number of Hits/Trial	22
Figure	2.3	Frequence Plot of Number of Hits	22
Figure	2.4	Cumulative Success Ratio of Subject (both machines	
		used)	23
Tee			
Figure	2.5	Accumulative Probability of Succsss on Machine 1	.24
Figure	2.6	Accumulative Probability of Success on Machine 2	25
Figure	2.7	Hits vs Trial Number for Machine 2	27
Figure	2.8	Total Number.of Hits Within a Tri al	29
Figure	3.1	Selected Parameter Totals Listed by Trial Number	32
Figure	3.2	Color States of Machine 1 During the Experiment	34
Figure	3.3	Color States of Machine 2 During the Experiment	35
Figure	3.4	Total Number of Passes of a Trial	36
Figure	3.5	Total Number of Passes Summed of Sample Number	37
Figure	3.6	Plot of Number of Hits per Trial and Number of	
		Passes per Trial	39
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Figure	3.7	State Transitions From Subject Choice to Future	
		Machine State		40
Figure	3.8	Distribution of	Yellows for Machine 2	42
Figure	3.9	Distribution of	Greens for Machine 2	42
Figure	4.0	Distribution of	Blues for Machine 2	43
Figure	4.1	Distribution of	Reds for Machine 2	@43
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Overview
An apparent phenomenon which defies the theory of probability occurs
when SLbject 2 plays this experimental game. He significantly exceeds his
probability of success, .25, by scoring over .29. The question that this
report addresses is: Is there a statistical or logical reason why he did
so well? The methodology used to attack this problem and the resulting
conclusions are summarized below. This summary can also serve as an outline
to this detailed report.
I. Statistical Analysis of the Machine Experimental Data
Pre-experiment data analysis discovered a non-random characteristic
through the examination of forward-backward state transitions (i.e.,
Red-Blue, Blue-Red). However, the coefficient of correlation between
the forward and backward states of .58 for the experimental data, .49
for Machine 1 data and .48 for Machine 2 data were considered low
enough that this approach was dropped. Pre-experiment state transitions
had a coefficient of correlation of .93.
The experimental data randomness analysis consisted of examining
the-distribution of color totals and the distribution of each color
taken over various combinations and permutations of the data. No evidence
of non-randomness was discovered.
II. Analysis of the Subjects' Data Responses
The subject's responses were analyzed with the emphasis on the
discovery of his strategy or the unveiling of a trend which would give
him a statistical advantage. The possibilities investigated produces
no solid reason how he was able to be so successful. However, in one
case there is a strong indication 1@@ he was able to succeed. It appears
that he was learning the states of Machine 2. The details of this are in
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the remainder of the report.
Miscellaneo us
The report contains a section entitled "Miscellaneous" for the
purpose of displaying detailed data which wasn't directly required by
the above more general analysis. Details such as how many successful
choices in the color red during the 50th trial were there, or what was
the relationship of the number of passes to the number of successes.
The terminology used is as follows: the term "trial" refers to the
string of machine states and corresponding choices from the time the
subject begins until he makes 25 non-passing choices. A sample.is a
machine state and/or subject choice (including passes). There are
(25 + passes/trial) samples in each trial.
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I. Statistical Analysis of the Machine Experimental Data.
Forward-backward State Transition Analysis SG11
In a previous memorandum (Memo ORD 2240-75, 12 June 1975 to
the question of randomness with the emphasis on state transitions as an indication
of non-randomness was addressed. The data used in the investigation consisted
of pre-experiment trials. The purpose of this section is-to do a similar
investigation using the actual data which occurred during S2's experiment.
Table 1 presents all possible transition frequencies. All transitions
should have equal probability.
YELLOW GREEN BLUE RED
YELLOW 204 199 199 216
GREEN 192 218 222 207
BLUE 211 206 228 222
RED 209 206 223 221
Restructuring into a two-by-six table as in Ref 1 produces:
Y/G Y/B Y/R G/B G/R B/R
FORWARD 199 199 216 222 207 M
BACKWARD 192 211 209 206 206 223
The conclusion based on pre-experimental data was that these state-pairs
show a very strong relationship between forward and backward transition
frequencies (coefficient of correlation =.93). However, computing the coefficient
of correlation, Ps2 actual data .58, it becomes apparent that the
degree of dependence is slightly reduced. Therefore the dependence of
forward to backward states can no longer be considered as a strong indicator
of non-randomness.
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The data used in the above discussion consisted of trials from both
machine I and.machine 2. Since non-randomness, made apparent by the state
transitions, clearly existed for pre-experimental data, the investigation of
the experimental data continued to include a search for this trend in the
individual machines. The transitions (including identity) are as follows:
Machine 1
YELLOW GREEN BLUE RED
YELLOW 96 79 88 92
GREEN 85 87 86 88
BLUE 85 82 90 87
RED 91 91 83 92
Machine 2
YELLOW GREEN BLUE RED
YELLOW 108 120 ill 124
GREEN 107 .131 136 119
BLUE 126 124 138 135
RED 118 115 140 129
Computing the two coefficients of correlation,
PI 4934
machine I
s2 data
and
P@ .4838,
machine 2
s2 data
it is obvious that the forward and backward transitions are even less dependent
than in the combined case. Thus ended the search for non-randomness through
state transition.
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As a by-product the following table is produced for general information.
BOTH MACHINES MACHINE 1 MACHINE 2
MEAN .SD MEAN SD MEAN SD
FORWARD 210.8 10.7 86.6 4.27 124 9.74
BACKWARD 207.8 9.00 86.2 .3.92 121 11.25
TOTAL DATA POINTS 3483 1446 2037
COEFF OF COV 5843 .4934 .4838
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Experimental Data Randomness Analysis
The machine data used during the S2 experiment h s been combined, summarized
and/or permuted in an attempt to establish evidence or-randomness or non-
randomness. If an obvious indication of non-randomness would have evolved
this task would be simplified because it would have become a closed form
problem (i.e., the solution would be - the data has.non-randon! characteristics).
_However_,_what-has resulted is thatvarious forms-af the Ai@a have been examined
with_aLl indiLating that the data is random.
Tables, plots and commentary are presented in this section to demonstrate
randomness and in some cases just to provide general information concerning
the machines data.
The distribution of the colors collectively and for each machine is
as follows:
Yellow Green Blue Red Total Mean
Machine 1 365 353 356 372 1446 361.5
Machine 2 475 505 538 mg 2037 509.25
TOTAL 840 858 .891 891 3483 870.75
Machine I was not used in as many trials as machine 2 (44 trials to 56
for machine 2), thus the difference in totals. The standard deviation of
binomial distribution with n=3483 and p=1/4 is 25.56 which would imply that
each separate number is reasonably close to the mean.
Accepting the distribution of the totals consider the distribution of the
colors throughout the experiment. The popluations used for this investigal-lion
consisted of the first 25 samples of each trial (100 trials total). This
population is acceptable since the distribution of its totals was reasonable
and since the performance of S2 was approximately the same (success-29.61%)
for this subset.
J
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The following three approaches comprise the strategy used to attack
the question of color distribution.
1. Each_trial,,J@bbreviated to 25 sample-s).a,s analyzed_separate interval.
Obviously this will indicate any bias within each trial.
2. The data (2500 sa
..mpl.es) is divided into intervals of five samples
each. This will indicate unusual-repetitions either within the
interval or interval-by-interval.
3. The data is reformatted into 25 intervals of 100 samples,where the-
nth interval consists of the nth sample in each trial.
The results of approach 1 is shown in Figures l.l.a, I.I.b, l.l.c, and
l.l.d.
The binomial distribution for this strategy (n=25 p=1/4) is mean 6.25
and the variance 4.69. The plots indicate randomness throughout the 100
trials.
The results of approach 2 are similar to approach 1 and are shown in
the four tables in Figure 1.2. The plots indicated randomness but are not
shown because of monotomy. The binomial distribution mean is 1.25 and the
variance .94.
The binomial distribution mean and variance for approach 3 is 25 and 18.75
respectively (Figure 1.3). A plot of the data (Figure 1.4) for the "RED"
case because of the concern for the higher variance and ranges. The 13th sample
seems to have an unusually high frequency of "RED" (44%). However in general
this investigation has not produced a significant non-random characteristic.
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Vow			
		sample size	100
		maximum	12
		minimum	3
		range	9
		mean	6.23 -
		variance	4.239494949
		standard deviation	2#059003387
		mean deviation	1.6314
		median	6
		mode	6
	15M		
	M		
	M		
	M	0	
	M		
	lom		
Number	PA	0 ()	
of			00

Yel I ow	1) 0
k () 00	
00,
VOW		11) 000 000	00 000
per
Trial		00 0	000
		0000	
	M		
_J_			
	Ni		
	0M	M M M M @k	M M
	0	20 40	6.0 80 100
			
		Trial Number	
	Figure	l.l.a -.Distribution of Machine	Yellows Over Trials
			
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		Sample size	100
		maximum	12
		minimum	0
		range	12
		mean	6.13
		variance	5.851616162
		standard deviation	2.419011402
		mean deviation	1.9404
		median	6
		mode	5 7
	I 5M		
			
			
			
			
	10 IM		
Number	W.)	00	(Y) 00
of	M	00	00

Green	M	00	
			000 00
per
Trial	5M 0	0 0000 0 1	0
			(H)
	M		
			00
			
	0&1	M M M M	ki M hi M M NI
	0	20 40	60 80 100
		Trial Number
Figure l.l.b Distribution of Machine Greens Over Trials
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		salople size	100
		maximum	
		minimum	
		range	to
		
mean	6.21
		variance	5.218080808
		standard deviation 2.284311889
		mean deviation	1.8194
		median	6
		mode	6
VOW	15M		
	M		
			
	M		
	M		
Number	IOM	o	
.of	M		
Blue	14		00
Per	M
1	0 o oo 00	000
Trial	1
4	() 000	
	5M	00	000 00
	kf()		0000
	M	00	
			
			0
	om	M M M hT	M
		20 '40	60 80 too
		Trial	Number
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		Sample siZe. 100
		maximum 12
		minimum I
		range 11
		mean 6.43
		variance
4.631414141
		standard deviation 2.152072058
		mean deviation 1.7158
		median 6
		mode 6
	15M	
	M	
14W	M	
	M	
Number	lom	
of	M	00' 00
Red	Nj	00
Per	M()	0000 00 oo 0 0 0
Trial	M	0000 o o 00 00 oo 0o 0 0
	5M	00
	,M	0
	M	
	M	
	M	
	
0M	M M M
M M M
	
0	60 80 100
20 40
		Trial flunber
low,		
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qqq Ryle;nS?
		r
1DUtlon of Machine Reds Over Trials
		9
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sample size	500
maximum.	5
minimum	0
range	5
mean	1.246 -
variance	0.9594028056
standard deviation	0.97949,10952
mean deviation	0.784848
median	I
mode	1
Distribution of Green	
-
sample size	
500
maximum	5
minimum	0
range	5
mean	1.226
variance	0.9969178357
standard deviation	0.9984577285
mean deviation.	0.804512
median	I
mode	I -
'Distribution of Blue	
dstat grp;<-J3	
sample size	500
AW maximum	4

minimum	U

range	4
mean	
variance	U.9513,DUIU14
standard deviation	0.9/84429985
mean devi,ation	0.19211)2
median	
mode	
@'Distribution of Red	
,sample size	500
maximum	5
minimum	0
range	5
mean	1.286
variance	1.026256513
stan'dard deviation	1.013043194
mean deviation	0.823216
median	I
mode	I
	
Figure	
	at a Time
10	

ApprovegFcy
t)	5@11A-RDP96-00787RO00200150011 -4
maximum	31-
minimum	19
range	12
WNW fnean	24.92
variance	10.57666667
standard deviation	3.252178757
mean deviation	2.6304
median	24
mode	24
Green Distribution	
sample size	25
maximum	35
minimum	15
range	20
mean	24.52

variance	24.59333333
standard-deviation	4.959166597
mean deviation	3.9392
median	.25
mode	22 25
VIAW
Blue Distribution
sample size 25
maximum 34
minimum 19
range 15
mean 24.84
variance 14.47333333
standard deviation 3.804383437
mean deviation 2.9664
median 25
mode 26
Red Distribution
sample size 25
maximum 44
minimum 16
range 28
mean. 25.72
variance 26.71
standard deviation 5.168171824
mean deviation 3.3664
median 25
mode 25
Figure 1.3 Distribution of Machine Colors When Samples are Taken 100 at a Time
(One From Each Trial)
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45M
M 0
40M.
M
M
M
35M
M 0
30M 0 0
M 0 0
M
Number M 0 0
of M0 01)
Red s 25MO 0 00 0
M 0 0
M 0
M 0 0 0
M
20M 0 0
M
M
M
M 0
1 5M M M M M M M
0 10 20 30
Sample Number
Fig ure 1.4 Distribution of Machine "Reds" when the Samples are taken 100 at
a time (one from each trial)
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Approach 1 has been repeated for Machine I and Machine 2 separateT y to
check for abnormalities. The binomial distribution mean and variance are
as follows:
Trials Mean Variance
Machine 1 44 11 8.25
Machine 2 56 14 10.5
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Machine 1		
Machinp 2	
	'Yel low		
sample size
WSW	25	Sa'mp I esize	25
maximum	16	maximum	19
minimum	7	minimum	7
...range	9	range	12
mean	11.4	mean	13.52
variance	7.75	variance	7.51
standard deviation	2.783882181	standard deviation	Z.740437921
mean deviation	2.224	mean deviation	2.176
median	0	median	14
mode.	12.	mode	15
	Green		
sample size	25	sample size	25
maximum	
17	
maximum	24
minimum	4	minimum	8
range	13	range	16
mean	10.68	
mean	13.84
variance	9.726666667	variance	12.12333333
standard deviation	3.118760438	standard deviation	3.5669-7818
mean deviation	2.3584	mean deviaticn	2.7808
median	11	median	.13
mode		mode	13

sample size	Blue
25		
	
15	sample size
."	25
maximum		maximum	25
minimum	3	minimum	10
range	12	
range	
15
mean		
mean	
14
12
variance	7..726666667	variance	.
943333333
8
standard deviation	2.779688232	standard deviation	.
99054064Z
2
mean deviation	2.3072	
mean deviation	.
1.984
median	it	median	
14
mode.	8, 12	mode	15
Sample size
maximbm	25 Red%	sample size	25

minimum	19	maximum	
21
range	4	minimum	I I
mean	15	range	10
variance	11.6	mean	14.52
standard deviati	10.5	variance	10.01
on
mean deviation	.3-240370349	standard deviation	3.163853404

median	2.4	mean deviation	2.6624

mode	1.2	median	13
	12	mode	11 13
			

Figure 1 AM~N9*F9b	3/04/18 CIA-RDP9

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1	6-00787ROO0200150011-4	
	.
ution
for Machi	
e 1 and Ma
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Tn Tyinl Qmc4e	c
ne 2 on a T
@
I al	rial
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Best Strategy
Based.on the above analysis what is the best strategy to pursue? No
good strategy is available based on the randomness of the data. The best
possible strategy based on the above transition matrices is:
1. If the subject can't distinguish between machine then press blue
when blue appears, else pass.
2. If the subject can distinguish them on Machine l-, press yellow
when yellow occurs, and on Machine 2 press blue when red occurs.
For all its worth, of the existing data the following success would
result 26%, 26%, and 27%.
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Analysis of S2 Data Responses
The attempt here is to discover a reason for S2's success at responding.
The investigation was unable to give a definitive reason for his success.
Although no strategies were uncovered there was in one case a indication that
the subject was learning.
Two major approaches have been taken in this investigation. They are.
as follows:
1. Strategy of S2 Was there any trends in the way he guessed? Did,, 4,;.-
he respond based on the previous state of the machine?
2. Hit analysis - Did the subjects' hits (correct choices) increase
within a run; did it increase from run to run (i.e., was he
learning?)
Strategy of S2
For general information and future reference the first figure (Figure 2.1)
presented is the actual choices,. One item of curiosity from this is that
w@hen he-passes, he tends to do-it-in-st-r-1p,gs. This characteristic of course
wasn't pursued because of its insignificance to this report; however, observations
like that are pointed out throughout the report as possible importance to those
in the field.
Total Color Choices
The distribution of S2's color choice totals are shown below.
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0 21 1 Ci 2 o t o i@ 1:-Z, o o 2 0 7@ 0 o,-*:!:-,, 0
1 2 0312 1 0:330:::,
0 12 0:- 2 1 2 2 1 2-
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0 2 1 C 111 0, 2 C 11 : 3 F 1, 3, F i C i C 10:, D I
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31 7-_-,. 7777 7-77 777777170710 7 74 1-77 773 0 0-7-3-7, t -277 71-7-7-1 0,'3, 0,1:-,-(,7 173 7 0 t :3
-7
3777707-77-J."701777 7 1 0
7 7 7 7 7 7 7 7 7 022 0:--: 0 1 0 1:-,, 0 1
17777777 3-7777-7 0 1:77 077777-7-777,--) n 1:3 1313 F `323 0:32 0
0:3 f- 7777377 0 10:- 1 r r t I I Z,
'0 023 0 171 1 13 0 -1-77 7 -17- 7 1.` 7 7 7 7 7 13 0 1 S 0 2 .71, 2 0 13 o
0 7 77 7 "1 7 0 10 10 2 0 S 10 2:@ 0 7 0:3 7%, 02 7 C, 7 3 0 7 71 7 717 7 7 1:3,
3 0 7 13 7 7 7 0 3 7:'0 71" 7 0 --1 7 7 7 7 -73 2 1 -7 7( 7 7 7 7 77, 7 7-1 7 7 7 Tl 0 3 13 C, 7 7 7 '17 7 7 77 7 7 7 7 7 -7,3 -7 0 .3
-7 -Y
ril- 7777777-CIO
3 10 3 7 2 2 10 13 0 1 10 1 0:-::@ 7 0 1 G,
3 t 3 1 0 2 3 t ::-, 0 1 0 12
13 0-37@-3713 73 0 13 0 1:7;'t--D--,T77 1777@--.,-r 77-777777 07-@) 1 2 107.1
J
-17: '7 3 1 7 2 1 T 7 -17 -
13731 1 177 1 -11777777 7 7 - 03 -7 3:7: 1 -7 0
7@ 17 -1
13 2 3 7 0 t:3 o -7 -7 n 7 2 -3, 1:'-:, 10 1,@E- 7 7 7 1 *3 1 3 7 7 7 7
f 7 777 17 077731 727' 12 0-7 13
13 7 771- 17 7 7 7 7 71 7 r2:-: II C1 2 17 17
-17 0 1 071~l-201--l-~*~7C"-~~277C)C;~Ci,
0 T' 113 7 0 1 `:, 11
D
13737 0 1 ci---, 031 (1711 -7 L2., n -.-:- 11 0t 0 0 237 7 3:
I n- 0 17 7 10 2 *3 7 3 7 1:-, (1 -1 ci -7 0@3 '-'C':--- 7:3 0
D
2 1) 3 0, --- 32:'-:, 113: -:,, A 2, 12 12 133 3 1
2 3 0 T477 0 I'L:--'7 3 2 12 0 0 T-: @i 0::@ C, C,
Vigure 2.1 Subject 2 Color Choices for First Fifty Trials (0-yellow, 1-green,
2-blue, 3-red, 7-pass)
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17
K-3031 4&2,jj@ fiE @J@J!q @@qi@-391t@qP?f@A"7 ROO 0200150011-4
031137
20703123070231703030330133703
30170102031730730300330313713
010077773737073037771737'77273377310770777130777373773
20707370731777370077037370002731777707077777073777777377773
01730330320370330327013703013
303717033207303073773013023737203
03737373033730321732333771737337,07371
23707377313033333703773'173707173777377373270
13107303737730103333370737313707700
33373707730730373333130373370707770733
033037737'70333'73377'77077777327777301027337333
030303720000377373377707737733030332
33032133270323233130121330
10701101301101313030230123
30070330072373003037177713777'7033002
031337373'7030003200030001003
302332131000001371303703037770
77201771007703072370.*313-131013777377177777303
33717 10177 1137 1300217333733030733
307173'73717077130117303707301373370071
03303203020071027107377121270703
032313273203730237703311~10077700
3317370'*1371071317331331730117207073
27131310732703327773 1177130323303
3000373300033003710303071330
301270013333013077737077373303377770770
03037030370737323li370710732001773
37733070072000-770300373130003002
13200200030030@770300731723370
30707207020773307033030303777377737377073
07077730703700377777707'731707330307307077770737373
00707737377003073730*777'17770737'1'7'77737773770300077773333
1301037132010717301002720073723
3101310317001300001730073020
037'777200707'73100770707373007200730700700
30300007100000232113002002
3031301301320130231033003
2301203130120310311303120
3013023103173713073032300131
3013013013201302 101302303
130231032303713273031030130
3010310310773230313073021331
310313031737701373001330033777713
313010303,10330307377070037717003
023130332013700137230201330
0217373103101303700073027777310373
137073107103702373132710331073703
331300301707301070700371073700713
Figure 2.1 (Continued) S2 Colol- 'hoices for Last 50 Trials
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	Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
	Yellow	Green	Blue Red
MAW	Total Times Chosen 881	411	237 971
	% of Total 35%	16.5%	9.5% 39%
	The first inclination is to try	and determine h	ow his strategy of choosing
	so many yel.lows and reds benefitted	him. Examine th	e following table:
	Yellow	Green	Blue Red
			60
	Total Number"of Hits 255	127	5er 292
	% of Total Hits 35%	17%	8% 40%
	% of Success in Color 29%		25% 30%
	(Hits - Corr	ect Choices)	
	As can be seen his results with blue	are significant	ly lower than the others.
			
	However, assuming the probability of	success to.be .	24 and using the binomial
	distribution the expected value =69	and the standard	deviation = 7. The
	inference from this is -that the 60 B	lue hits are not	a statistical abnormality.
low	However, it is curious that he did s	o much worse on	his lowest preference.
	State Transition Color Choice		
	This investigation consists of	examining the st	ates of the machine verses
	the choice on the next sample of the	subject (i.e.,	if the machine shows "red"
	does the subject consistently choose	one color on th	e next turn,). Consider
	the following table:		
	M
@"BS	achine	
	Yellow Green
MAC\H	Blue	Red Pass % Pass
S	Yellow 106 119	69	314 210 26%
U			
B	Green 177 2,5		316 252 30%
J			
E	Blue 241 9§	27	198 302 35%
C			
T	Red 322 157	65	97 218 2579
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Approved For Release 2003104118: CIA-RDP96-00787ROO0200150011-4
	The	subject obviously avoids repeats	(i.e,, he	assumes the	machine
	.-vton't repeat a color) which, ba	sed on -the	machine data analysis,	isn't a
	strategy	which would give him a	statistical advanta	ge. Previous	analysis
	showed that identil@'transition	s are approximately	equally proba	ble as
	nonidentity. Notice also that	he passes 35% of the	time after s	eeing a blue.
	The	same state transitions	are shown	below sep	arated by mac	hine.
		Yellow	Green	Blue	Red	Pass
M	Yellow	48	49	25	150	83
A						
C	Green	62	13	35	153	83
H						
I	Blue	105	36	10	78	115

N						.
E	Red	133	72	30	58	64
1						
M	Yellow	58	70	44	164	127
A						
C	Green	115	12	34	163	169
MWH						
I	Blue	136	63	17	120	187
N						
E	Red	189	85	35	39	154
2						
The negative state transition (i.e., relationship of the subject color
choice to the machine state on the next sample) is considered too bizarre of
a concept to be presented in this section. Results of that investigation
ii'found in the section entitled "miscellaneous"
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Approved For Re.lease 2003104118: CIA-RDP96-00787ROO02001500.11-4
Hit Analysis
This section.is significantly more important than the randomization
analysis of the machine data. The reason is that if he is not learning from
the machine or he is not taking advantage of bziases then the discovery of
such non-randomness is of little value to the overall analysis.
Learning from Trial to Trial.
The question of whether the subject learned from trial to trial can
best be answered by examining the following three plots.. The first is the
number of hits vs. the trial number, the second is a frequency distribution
of the number of trials vs. number of hits, the third is the accumulated
probability vs. the trial number.
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	Approved For Release 2003/04/18 CIA-RDP96@00787ROO0200150011-4
	15M	
		
	N	
	Pi	0 0 0
	F-1	0 0 0
	1 CIM	0 0 0 0
	M	00 0 0 0 0 00 00 0 0 0
Number	r-I	0 0 0 0 0 0 0 0 DOODDO 000 0 00
of	P10	D 00 0 0 00 0 0 0 0 0 0 0 000 0
Hits	r1i	0 0 0 0 000 Goo D 0 0 OD 0
	5r,10	0 0 0 0
	ri	0 0 0
		
		0 0
	rl	
	Orl	M PI r-I rl Ill M r1l rl ri M
	0	20 40 6- 0 8 G 100
		Trial Number
		Figure 2.2 Plot of number of hits/trial
	C25 M	
	M	
		
	M	
	M	
0
	M	
		
	1 C5 M	
	M	0
Frequency		
of	M	
Hits	M	-

per	
10M	I
Trial		
	M	
	M	
	M	0
	M	0
	M	
	M	0 0 0 0
		
	M	
	C1 M	0 M M M M MD 0 0 0 DIMO 0 0 0 OM9 0 D
		5 10 .15 20 25
		Figure 2.3 Frequency plot of Number of Hits
		
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		22
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
0. 30M
M @0- 0
M 0 0
M 0 0 0 0 00 0 0 000
0 2 9'M 0 000 (M 00 0 000000 0000 0000000 00
M 0 MY) 11) 0 0 0 0 0000 0
Cumulative 0 0 0
Probability 0 0
of M
Success 0.28MO 0 0
M
M 0
M 0 0
M
0.27M
M
M
M
M
0.26M, 0
0.25M
M 0
M
M
M
0.24MOO M IIA M M M M M M M M
0 20 40 60 80 100
Trial Number
Figure 2.4 Cumulative Success Ratio of Subject (both machines used)
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Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
M
0. 3 1 M
0. 30114
M
M
NI
0. 2 9M
Accumulative
M Wi
Probability X) 6@
M
M o'
0.28MO (Y)
0. 2 7 h4
'War
0.26M
0.254
0. 2 4AM- 0 (N JA M M M M M NI M IA
0 10 20 30 40 50
Trial Number
Figure 2.5 Accumulative Probability of Success on Machine 1
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Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
0. 3 Oki
000;
0.29M 0
A, J00 t C
M
'o ()(Y
M
M
0.2814@)
M
0. 27M
M
M
M
M
0
.26
M
M
Accumulative
M
M
0. 2 514
M
M
0. 2 4m 'o-dM Vm M M IV M 14 M M M M xf
0 10 20 30 40 50 60
Trial Number
Note: V Points at which he switches machines
Figure 2.6 Accumulative Probability of Success on Machine 2
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Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
The first plot (Figure 2.2) demonstrates the randomness of the number
of hits while the second plot (Figure 2.3) demonstrates the frequency
distribution takes on a "normal" appearance.' The accumulative probability plots,. at
first glance,indicates that the su.bject was in a learning mode for the
first fiv.e trials. A closer examination of the data indicates that this tan
occur naturally as part of the statistical distribution.
The first three number of hits points are 7, 5, and 6 considering the
first 75 points as the population with probability of success = .2936
(the final probability) then the expected value is 22 (using binomial
distribution) and the variance is 15.55 (S.D=3.9). As a normal deviation
from the m6n (i.e., using normal distribution approximation P(x`<18)=.l3.
Although the observed learning can be rationalized as a natural statistical
deviation it warranted further investigation. The plots of the accumulative
probability of success for machine 1 and machine 2 are presented in Figure 2.5
and Figure 2.6. The plot for machine 1 (Figure-2,5) is a typical sinesodial
decreasing amplitude convergent curve. The plot for machine 2 however, is
-@'Very suspiclous in terms of learning. The major peaks of the curve (at
approximately trial 10, 23, 40 and 56) are increasing which implies his
probability of success is continuing to increase instead of converging on
one point. @hother interesting point5i-st-hat the points at which he switches
onto machine 2 areI, 9, and 36.
Also of concern is the sharp upward turn during the last 8 samples.
The hits totals for this period, starting at sample 49 is 10, 10, 8 11, 6,
8, 7, and 11. for a total of 71 hits out of a possible 200 for a probability
of success of .36. Once again using the binomial distribution and using the
probability of success of .29 (the cumulative probability up to the 49th
point) the expected mean is' 58 and the standard deviation 6.42. Using the
Nw@
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Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
12. 5M
,%W M
M 00
10. OM
M
M
M
00 00
7. 5M
Mo 00
4-3 M
.I-
M 0000
4- M
0 5. Oki 0
M
M
M
M
2. 5M
M
M
M
M M M
0. OM M
0 .20 30 40 50 60
Trial
Figu re 2.7 Plot of Number of Hits on Machine 1
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Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
normal approximation the probability P(X 71)=.02 of such an occurrence is
quite low.
Although there are only 56 data points in this population and the
apparent abnormalities are statistically possible (with low probability) this
investigation concludes that the subject's learning for this case must be
flagged as a real possibility. Figure 2.7 (Number of hits on Machine 1) has
been added to provide clarity. It appears that the subject just didn't have
"low hit" days toward the end.
Learning within a Trial
The question of learning within a trial or run has been investigated e
by summing the number of hits of the Ith sample for the t4un. The results
are somewhat distorted because of the inequitabl.e distribution of passes.
The lower numbered samples have significantly more hits because of this.
A plot of the number of hits per sample vs. sample number is shown in Figure 2--7-
Notice that the first sample has a value of 34 hits. This means that
everytime he ists down for a new 25 sample trial he hits 34% of the time on
his first try. With this in mind along with the rest of the data points, it
is obvious that the subject doesn't learn throughout the trial.
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Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
40M
M
M
MO
M
30M
M
M
MOO 00
M000
Number 20M
o f M
Hits M
M
M
I OM 000
M
M 00
00
M Of)
0 IM M M M M MO
0 .20 40 60 80
Sample Number
Figure 2.B Total Number of Hits Within a Trial
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Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
Miscellaneous
Numerous arrays of data have been examined for the purpose of obtaining
some insight into the data. Some of the data is being printed herein so that
the data can be examined more closely if desired.
This first table is presented for use as a quick reference.
Number
Last of Machine
Day Trial Tracks Used
8 8 2
2 16 8 1
3 24 8 2
4 36 12 2
5 44 8 2
6 52 8 1
7 56 4 1
mar
8 64 8 1
9 68 4 1
10 72 4 1
11 76 4 1
12 80 4 1
13 84 4 2
14 88 4 2
15 100 12 2
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Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
The following displays are presented below with little commentary.
I. General trial summary (Figure 3.1). Each trial (25 choices) is
listed with the following information.
A. Machine used (1 or 2)
B. Total number of machine states in each color (i.e., 6 yellow,
6 green .... for each trial.
C. Total number of subject choices for each color for each trial.
D. Total number of hits for each trial.
E. Total number of passes for each trial.
F. Breakdown of hits by color.
II Machine data for machine 1 and machine 2 separately (Figures 3.2, 3.3)
Just by examining these displays it may be possible to glean
meaningful information. For example, machine 1 was used for the
first 8 trials during which the first state of each trial was a
yellow or red. If the first sample of each trial is most memorable,
perhaps this is responsible for the subject's obvious preference of
yellow and red (see Section 2 - Analysis of S2 Data Responses).
III. Plots of the number of passes made.
A. Number of passes vs. trial number (i.e., trial is 25 or more
samples) (Figure 3.4)
I.B. Number of passes vs. sample number (Figure 3.5)
31
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Approved For Release 2003/04/18 : CIA-,RDP96-00787ROO0200150011-4
		mach	mach	mach	mach	sub	sub	sub	sub	numb	num	hit hit	hit hit
trial	mach	yell	gren	blup	red	yPl	arn	hlu	red	hits	pas	yel qrn	blu red
1	2	6	6	2	11	11	3	5	6	7	0	3	0	0 4
2	2	5	9	4	7	10	3	4	8	5	0	2	1	0 2
3	2	7	8	6	4	7	4	6	8	6	.0	2	2	1 1
4	2	7	4	10	4	10	3	4	8	8	0	4	1	'2 1
.5	2	5	6	11	3	11	4	0	10	5	0	2	1	0 2
6	2	8	5	3	9	10	3	2	10	10	0	3	1	0 6
7	2	3	7	7	8	11	1	3	10	8	0	2	0	-2 4
8	2	6	7	3	9	11	2	2	10	9	0	4	1	0 4
9	1	9		2	8	.10	3	5@	7	7	0	4	0	0 3
10	1	5	5	8	7	9	6	1	9	9	0	3	3	0 3
11	1	6	4	7	8	6	6	3	10	2	0	0	0	0 2
12	1	7	2	7	9	9	5	3	8	6	0	4	0	0 2
13	1	5	7	4	9	10	3	2	10	12	0	3	2	1 6
14	1	4	5	11	5	10	2	2	11	8	0	2	1	2 3
15	1	6	9	5	5	10	3	1	11.	9	0	3	2	0 4
16	1	6	2	7	10	8	5	4	8	5	0	2	0	0 3
17	2	10	12	7	7	12	2	1	10	7	11	4	0	0 3
18	2	4	9	9	11	10	2	2	11	8	8	1	1	1 5
19	2	8	9	-10	11	11	3	2	9	6	13	3	0	1 2
20	2	7	13	5	8	11	1	4	.9	7	8	3	1	1 2
21	2	9	8	9	9	10	5	1	9	9	10	3	2	0 A
22	2	13	12	9	9	8	2	2	13	5	18	0	0	1 4
23	2	9	9	15	12	11	1	2	11	7	20	2	0	1 4
24	2	10	9	11	..9	8	3	2	12	8	14	3	2	0 @3
25	2	3	11	7	8	8	5	5	7	2	4	1	0	1 0
26	2	10	4	10	10	8	6	4	7	9	9	4	0	2 3
IRW
27	2	11	6	15	9	11	1	0	13	12	16	6	1	0 5
28	2	5	6	10	11	10	5	2	8	7	7	2	1	1 3
29	2.	7	16	16	14	3	.4	3	10	8	28	1	2	1 4
	2	16	19	18.	12	8	6	1	10	8	40'	3	3	0 2
31	2	10	10	9	19	10	5	1	9	9	23	2	1	1 5
.
32	2	12	9	19.	12	8	7	3	7	2	27	2	0	0 0
33	2	11	14	20	10	9,	4	2	10	5	30	2	1	1 1
34	2	16	4	10	8	9	5	3	8	12	13	5	2	1 4
35	2	9	7	11	15	12	4	3	6	7	17	3	0	2 2
36	2	14	17	19	22	9	4	1	]1	7	47	2	1	0 4
37	2	5	16	13	11	9	5	2	9	6	20	0	4	0 2
38	2	5	7	8	.9	7	8	2	8	7	4	1	3	0 3
39	2	7	7	9	6	6	6	3	10	9	4	1	3	1 4
40	2	'11	13	10	10	7	6	2	10	9	19	2	4	0 3
41	2	10	14	9	.12	4	8	2	11	4	20	-1	1	0 2
42	2	11	11	7	9	4	7	3	11	9	13	2	3	0 4
43	2	15	13	14	11	4	9	3	9	5	28	0	4	0 1
44	2	10	9	11	8	8	6	4	7	11	13	4	1	4 2
45	1	12	9	7	8	10	6	2	7	8	11	5	1	1 1
46	1	5	6	9	7	4	4	6	11	6	2	0	0	2 A
47	1	9	10	10	4	8	6	2	9	6	8	3	2	0 1
48	1	9	10	7	6	8	3	4	10	6	7	2	1	1 2
49	1	7	10	6	2	4	6	6	9	7	0	0	5	1 1
50	1	9	12	1	7	Q	3	4	9	6	4	3	0	0 3
														
		Ajw3rove@
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WHO
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P -.00787ROO0200150011-4

T
f
Y
T		
		FIgure	.	ec	e	a e e	r
o	a
s	iste	d by T	rial	Number		
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Approved For Release 2003/04/18 CIA-RDP96700787ROO0200150011-4
		mach	mach	mach	mach	sub	Sub	sub	Sub	numb	num	hit	hit	hit	hit
,rial	inach	yell	gren	blue	red	yel	grn	blu	red	hits	pas	yel	qrn	blu	red
51	1	6	5	10	8	6	5	6	8	9	4	2	.2	3	2
52	1	7	15	11	9	8	5	1	11	8	17	3	2	0	3
53	1	11	5	7	6	9	3	3	10	6	4	3	1	1	1
54	1	6	4	7	12	9	5	1	10	9	4	2	2	0	5
55	1	13	14	12	14	8	4	1	12	7	28	.0	2	0	5
56	.1	12	14	19	14	12	2	2	9	6	34	3	0	1	2
57	1	8	2	11	8	9	3	2	11	8	4	3	0	1	4
58	1	6	4	11	12	8	2	3	12	6	8.	1	0	1	4
59	1	11	5	15	6	4	3	2	16	8	12	2	1	1	4
60	1	11	11	11	11	5	2	2	16	8	19	3	0	1	4
61	1	10	8	9	8	8	4	O	13	8	10	0	1	0	7
62	1	13	6	9	10	7	1	@
0	1!	7	13	3	0	sO	4
63	1	10	18	'10	7	6	1	2	16.	4	20	2	0	0	2
64	1	10	ll	6	9	10	0	2	13	8	11	4	0	0	4
65	1	7	9	2	8	4	4	5	12	8	1	1	1	1	5
66	1	3	12		7	8	9	2	6	8	1	3	4	0	1
67	1	8	10	10	8	11	2	2	10	8	11	3	1	0	4
68	1	10	4	5	9	13	2	1	9	7	3	4	0	0	3
69	1	10	a	4	8	-10	4	2	9	9	5	4	1	0	4
70	1	9	6	12	17	8	6	2	9	4	19	0	2	0	2
/I	1	11	7	7	8	5	7	1	12	7	8	2	1	0	4
72	1	7	9	13	9	8	7	0	10	3	13	1	1	0	1
73	1	11	6	5	.,10	10	4	5	6	9	7	4	1	2	22,
14	1	4	12	8	8	8	4	4	9	6	7	0	2	1	3-
15	11	.9	11	7	8	5	B	1	11	7	10	1	3	0	3
76	1	8	14	5	6	4	6	4	11	10	8	2	4	1	3
77	1	11	3	8	6	12	2	0	11	9	3	7	0	0	2
18	1	9	9	10	11	9	3	1	12	6	14	3	0	0	3
79	1	7	8	7	12	9	4	2	10	7	9	2	2	0	3
80	1	8	6	10	8	.14	1	2	8	8	7	4	0	1	3
81	2	13	4	8	5	12	2	3	8	10	5	7	1	0	2
82	2	6	.14	10	11	11	0	2	12	8	16	2	0	1	5
83,	2	7	10	17	16	13	1	0	11	8	25	3	0	0	5
84	2	14	12	16	14	12	0	0	13	'1	31	3	0	0	4
85	2	7	7	10	7	9	6	4	6	6.	6	2	2	1	1
86	2	11	7	4	6	12	6	1	6	7	3	5	1	0	1
87	2	13	13	9	6	17	1	2	5	8	16	5	1	2	0
88	2	6	3	8	9	14	.3	4	4	7	1	4	1	1	1
89	2	6	5	8	6	--8	5	2	10	6	0	2	V	1	2
90	2	7	7	4	7	7	7	4	7	6	0	1	3	1	1
91'	2	9	10	7	2	7	6	2	10	6	3	4	1	1	0
92	2	4	6	10	5	8	6	3	8	6	0	1	3	1	1
93	2	6	7	7	7	7	5	3	10	10@	2	3	2	1	4
94	2	5	6	4	13	7	6	2	10	10	3	3	1	1	5
Y5	2	7	5	10	11	7	6	0	12	8	8	2	1	0	5
96	2	7	9	7	9	11	4	0	10	11	7	5	1	0	5
Y7	2	8	8	6	5	8	4	4	9	6	2	2	1	1	2
98	2	7	12	10	5	9	5	2	9	8	9	3	3@	0	2
99	2	8	9	8	8	7	6	2	10	7	8	2	2	0	3
100	2	9	5	9	10	12	5	0	8	11	8	5	3	0	3
															
Approved For Release48851%Z19 8&qftb%@-Cb687ROO0200150011-4
33
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
U 0 3 1 CI 0 7.312 12'0 3@2 t 10 73.
n
SC1 -7.@ i:-
2 2 -2 2 10 10'--, 3 1 C i 1 3, 3 2 1 :3 A
22 0:33 11 C'L'7-j 10 22 2 3 3 12 A 0 0
2 _3
3 i.-j 3 02, 2 OL2,'-:, 2 2,---., 10 Cr0 0:-': 1,-, 2
3, 13 12 0 2 3 0 F, 1, 1 :'3 13 @:, 2 10 C, I
2 2 2 11 L2, 23 1 C, 2 2 0 0:3, 12, 2 10
1,2, 2 11-3 1110'. 0 1'--' 2 2 12 0 F1 12 0
0 -":" 2 2 112 321, 0 21, -2,C2, 110 10 0 "7: 1 e. CI 12 2 102 Z. .3, 0 0 1
0 F1 11 22@ 3 1 *2 2 0 0 13 10:3 -@:' 0 0 2-`2 12 OER 3 G (i A I ']; 0 1 1
I .--: 0 2 2 3 10 1 1-12-2', 1,--: 12 i? 1? 1 1. --@ F - r, s
.3 j -i. 1@1 "
2 1112 0 1110 2 C 12, 22: 1113 2 1 1 T -, 2 110 0 7: rC
Ci 3 0 0 2 0 02, 12 2 11110'2 i '2: 10 110 1
Z., 2 2 11 'L2 10 A 12 1 A'2 12 0 10 10 0 1 :_--, I
1111 0 10 10 10 121' C1 "I'S' 10'2'3 10 10
0 12 0'2' 1 2'--@"3 2'32-, 0 2"22 2:], 1 "2 0:*-:::-3 n 13 1 0
I T-34 12 12 3 2 0 0 '-3 111 ijk---.@ 23 12'--" 2 110 110 12:11, 13 -2
71 -
13:.-:, 10 1 ID *L21 2:3. 12 02 0 G 0 0 0 12 - 11 A --, -3 2 2
, - - - 'Cc-
3 2 13'--, 13: -32: --- @ 3 1 ;2 F 1 2.'_3 2 3 0 C 12' 1 : -3 C i "D 2 C I -- "
2 11 1:--; 1110 31-12 3'--'0'--, t .10 0 .2 1 - I A 1 -11 - 11 j: 3 C j It t 2 2- 2 2- C 112 2 '2-- 1113 2 C
"L=-'2 I =-- C 122 1 C 12 2 C 112 C 12 1 2, 2 12, 2 0 C 12 2 C t I 111112 112 2 0 C 12
0 il 2 t OL=-, f 13 22-' 2 3 2 1,32 0 Ci:--- 1- 22'2 1-1
1 22:--j.2:---, 0-3-2, 1:3 @-22 1'2, 0 0 0:3, 2
Ci,,:' *2,2@ G 0 2-, 0 L2, '-':, 2, 12 0 212 ":: 2 0 1) 10 0 2, 2 2 2 12-, 0 1
2212 110 13 0 Fl*-,'I:--: I 1 *3 0.3 "12 112' 12:3 0:3@222 C13 I I 1 2 C12 1:-, -
L:@ D 2, - 3
'D
0-221132, fi 0 0 02:--,-', 112 03 t222 I:D 0--. 0 t 0:--, A IL I
- - " !`2 17--' 1 F 1-1 10'3: 3 3 `3 C' 1-12 2 i L- :3 2 cj::.
10 1103,:-32' 13 1 1
0-13371 111 A'2273 02 0 0 0 0 12 11 t 1 2*L:-:,:3 I 1 1122 112 110 10 G 12 1
2 0 3 111 0 2 11 G 0 10 '3:'-:,, 12 2 0 1233 0 10
13 113 10 0 1:130 13 1.23 3 02 0 1 CI L-
J -1 2 1
101 1"31 -1 .--, @-:' 3 L-, 12:7:' 2, 111110 11:
P.: -, 02D 0 110;2 C 112 1 1 : 3 1 ; ? -3 12 12, 2 10 1 2, 0 3 113
12:--; 0 2 0 0 A 02, 0 2, -3 2 10 "D 10 0 .2 12 i-r-3,
I z - 1 7)
10 1, 1 @---'O 0 3 2 2 0 1 `3 0 0 3:_3 1-13 0 11-1 12 1
1 '-:,2 2 2 3 3 jD 3, 3 . 0 1 c: , 0 2c'-'--': 2: 7-32 13 1 t 2 12
11223:3 0,22 CH) 1 UF 0 0:3 10 1-
2 1 0 02:3'')@'-:;- L-2 10 1 1: :2 1 2 12 1122, 0"22 Cl:---'
10 122 0:3, 13 2 0 13:3 1 0 1- 1.0 0 2 0 0 2,-:3
:3102,2132, 1 12"'D 013 12: tr2, 0I Cl'-:' 1@:_: 1. 1 0@---". Cr-3-2 000
.-1 . :' -1 i 13 112 0 t 3 0:.-:,
*':, 10 11 t 122@:-%- F I t I 110:-3 10 C " -1
2
0 C, C, 1-122,3 0 21- "@ I-' F 0 2,-!,D I CI CI I I
J
:2, rj 2 @3 1 A1:::, 2:::,. 112 10 2 0 1 ':'12 0 0 1) 10 2:3 2 2 2 3
3:13 1., G 11 :3 f i 1 '3, 1):-: 10 12,2 2 10 :3 2, 0 CI .3 22,
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
Figure 3.2 Color states of machine I during the experiment
(0-yellow, 1 qreen, 2 blue, 3 red)
@4 i603/04/18 CIA-RDP96-00787ROO0200150011-4
0:--" 0 ci:':, 2' cl I I 1 -2 1 1-11
0122 110 022'22 C, 0212
323 01223;z:,2222 0 0 1 111212
0:7:2 1 1-:-, FIE 0:--: 112,
0 12 11:3, 1:7-:22 3 3 2' -S@ 2:3 10 2A 102
:3 0 0 2:-3:'_:@ 2 10 0 1-:73 F :3 3 2 2 12 3
I 2--__112 3',"33 1 1! 1. 10 @1! 122 t I
C, 13 2:32:-_ 1. 0 2 0 1 1'112 2:3 C12'I-I I -=,:- -.:@ 1:-:, --:, I I:-
q CIE, C,
:32 13 0 111 02'E' 1 1-1 1-2-RO2 11 2:'-:'l 1-1 C '_-@:31 I I
0 CI 1 ":2-2 13 CI:_3 0 2 0 0 1-112' 1 CI 1 : 3:3' -, 12 ! `3 2 :-3, Ci E_, I
110 1 F' "21-111'-*:': 12 0 0 2 C, -3:31 CI CI 1:7-- 111:,:" 2:12 rl
2 7:
2, 1, - r- 2 2 0 10 1 1:3 2, 2 111 Y 112: 3`3 t 1) 1 1
212 1'31 C! 0 12'1_1@_"l 0 132 C'213-- t "Cl 02 C, 1- .2,
C12111131 10121':111
2-2' CI 02' 11:30 0 20 A 1-12 1-1 0232 t -'3:!:'
Z'
10 02 10'
2 3 r! 12 11 11 E,22:, 12;?. O'_- 0 1 2:2:'_:' 12 3 0
1:2310: :_31 12-201 0022@_-312'72:7211221 1:'3-123111
120:2111111201130131.1,3.
22 0 10*32 3 1 Ij I C, .-'10:3. r C, 1. 2 1 0_32f),31 23S, 12*,:.,
D
12 330 13 2 2 C1.3 2 -*--'2 102 2.2 2 1 C, 0,0 C, 2:---,, @7;1 2 112 C, 2 1"12 1'-7:,, 2'_--@
C, O'_32 13 2L2' 3' 10 10 '2' ::-!'12 2 --':, 2 2 @'3'___" 2 12 11112, 22, 1 f_r2 I Cr_-.@ 2 0 2,21 0 E*. 12 0 0 12, 12 0
:3 0212 02,2, 02 02:3 CI C;:--,''-i 1-11-1222 0 Oi_: 011 CI O:@*:-'_ I-11:_D23
N 2 0: 30223112 c-
_2 3 .3 - - c-2-30 0 0:3,:7: 12 3 11:'3 t I 1 120 2 0
2:_30 0 1110 2 1 ':3 2`12:---'! 2, 2 0 10: L_ C -D
t 1 I-f 0 12:- 02 1137'. 0 110 0:! -,2117"-, 17':,
3'---' 11 C I CD: z.: -2 1 '12 10 12:22 1 1113 111 '3 2 2 112 E, 3 2 C v. 1 3 1
L
:3 12 11 O'_3 3 3!) OF-31 2.12 3 2:,32 1 A F1
0 0 2 0: 3, 1 C 10 1 1 : 3 2 1 11 3 3 C i I _'-,2 CI 2
12 20 12 0 0 1:15j) 1'321 1 Ij 3 L_ C, 3 110 0 10 1 2'._3 '3 11 1-1 L'2' 22 1j:33L, 3 2 1
Z,
2 1 111 '2 0 11 C1 "':!:'3 Fi 112 0 0 il 2:3, 13 112 2:1,2 2 110 0 2 3 1
13 12 10 2 2 *-,'!':" 2 3 1 O'_31 0 1 0 0 11 1-111 3 (10 CI 2 0 12
2 0 0 2:3 0 11 -2, 0 0 11.23 2, 0 112 12 1::: n 2 2 10 0 2 2 0:7, 03 0 13 3 C, 222,
22 1:3 02 G2,:3 1 :3`3 021332 0 33 t 02 1:3 C, '_E':_-3 0 0' 12
12 3 0 (10 il C, 0 t O_-@ Fi 110 2 O'.-@ iR 2 rl,'2 i:221 CV--_: 2 O'D,
1122 1 2:_3*2;'-_' n 2 10 102 - 10,31112 10 t:-, 10:3
2 2 12 2`33 0:21, 0 1 0 110 13 2':@: _?, 12 1 R 0 2 0 2 2 12, -- 3 S, 22113, 2 2 1 .`:'E,:3,:3 r,
3
3 3 ',.310 2 0 2 2 0 2 0 Fj._11:32, 10 0 12 2 0 1 12'.:@, 12, 112 0 1:3, 12 1 2'_3 (1 "3' _-1 0 12 03-C, 0 1 L2, 1:33 (12,
13 03 2 2_1 01 1) t .3,* O,L:-:,:3 -_-"I 2 2 1 *2' 2 2 2 0 10 12
03 2 3.':-'3 "n 110 0 10 0 C, 10 12 10 2'_3 0 10:'-:' 0
I j::,nOCj2*;*:: I I 1001 0.,::;n Ot 2211 1212220t:321:_--:O20 CIO
2 0 C 1,, 1, C 1: 3: 12 3 2 C 1':-:, 112- 'D C 1, 0: 3 2
11 C 12: 0 2 C'R' 3R II , 2- 0 1 C! 2 C 1:,-; 0
2 10 3 0 10 0' 2-, 12 110 3 10 1:3 2
10 110 2, 1 2 12 0 1-! 112 0 1112 0 0 2
Ci 2 3 2, 2 12 11,2 2 2,32 O:'_:-2 -- I 10 12 0
03'3 2 -":' I t 2 1111 A'D, O'E, 0 2,:]: 0 12 2 S' 2-
113 0 2:3 2:3 A 2 1111 3, C1
2 0' R 1 13,,:! n 2 1:--, 2 0:-L:-
2,2223 L
31 0:3 0 12--32 0 12., 1 1:3:?2_, 0 110 O:_-;2D C"i 12
2122O']":-_:1230021 (100 1 Al 01:31:321
C, 31 2 0 10 0 2 13 12 2, 2 2 0 110`3 111 11 A _'_@ 12 2 12
111 0 3' 2 1 2 : 7' 2 12 3 0 C I I 1' 2 2 C I C 12 f I I i t I - 2 2 113
A -95qBq Fyr @Slease ffi3/04/1 -00787ROO0200150011-4
c ? : RADIP?6
rM lor s a es o m during the experiment
(0 yellow, 1 green, 2 blue, 3 red)
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
50M
M
M
M
M
40M 0
M
M
30M 000 0 0
IM
Number M
of M
Passes P11
2 014 000 0 0 0
M 0 0
M 0 0
M. 0 00 0 0
M 0 0 0 0
10 AM 0 0 0
NI 00 0 0 0 00 0 0
M 0 0
M 00 000 0 0 0 00
M Q
OM0000000 0 4 M M M M0 M
0 20 40 60 80 100
Trial Number
Figure 3.4 Total number of passes summed over a trial
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
35M
M
Approve*For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
.M
30M
M
M
M
M
25M
M 0 0 0
20M
M
M
Number 1 5M
of M
Passes M
M
I OMO
M
M
M
M 00
5M
000
M 00
M
MO 00 000
014 M M M
0 20 .40 60 80
Sample Number
Figure 3.5 Total number of passes summed over sample number
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
37
Approved For Release 2003/04/18: CIA-RDP96-00787ROO0200150011-4
C. Number of passes and the number of hits vs. the trail number
on one plot. Investigation of the hits/passes relationship
was dropped when the coefficient of correlation between the
two was computed at -.114
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
38
Approved For Release 2003/04/18 CIA-RD.P96-007871ROO0200150011-4
Pass
and
Hit
Total
50M				
M				
				
PA				
M				
40M				
M				
M				
				
				
30M				
M		(Y)		
M				
M				
				
2 OM		000		
M				
M				
M		00		
I
'A P		
P P P()		
P P
10 M PPP P	P P	P PP PP	P PPP()P	P ()
plipp PP P	PP P	PP PP POPP P()PPPPP	POO PPPPP	Op
NIPPP P P	PP	P P f)PPP PPP	P P () P	P P P
M		OOP 00 P O	PP 0	(Y)
M P .	P	P		() ()
	",A	M M	M M	00 M
0	20	@O 60	80	100
		Trial Numbe r		
0 - passes per trial
P - hits per trial
Figure 3.6 Plot of.number of hits per trial and number of passes
per trial
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
39
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
I V. Tables of state transitions which reflect the influence of the subject
on the machine. For color choices of the subject the table shows the number
of colors the machine has on the next sample. For example on the first table,
when the subject picked yellow, on the next sample 197 times the machine
state was yellow.
MACHINE STATES ON FOLLOWING SAMPLE
	Yellow	Green	Blue	Red	
Yellow	88	77	87	95	
Green	38	46	39	47	Machine I
Blue	27	28	24	24	
Red	120	105	99	112	
Pass	84	83	98	81	
Yellow	109	124	128	141	
Green	58	47	58	66	Machine 9.
Blue	25	32	42	30	
Red	121	125	136	102	
Pass	146	162	161	168	
Yellow	197	201	215	236	
Green	96	93	97	113	Both
					Machines
Blue	-52	60	66	54	
Red	241	230	235	214	
Pass	230	245	259	249	
Figure 3.7 State Transitions from Subject Choice to Future Machine State
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
.40
Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
V. Because of the possibility that the subject was learning the state of machine
2 the distribution of the colors are plotted in Figures 3.8, 3.9, 4.0, and
4.1. The only states used are those in which the subject didn't pass.
Therefore there is a total of 25 for each trial.
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
41
Approved For Release 2003/04/18 CIA-RDP96-00787ROO0200150011-4
10. Om
M
'ROW
7. 5M
M 000
M 00
Number M
of 5. OMO 00
Yel I ow M
M
M
M
2. 5M
M
M
0. OM M M M M M U
0 20 40 60
Trial
Figure 3.8 Distribu tion of Yellow for.Machine 2
12.5M
M
M
M
M
10. Om
M
MO
M
M
7. 5M 00
Number - 00 00
of M
.Green 5. OM 0 00
M
M
2. 5M
M
M
M
0. 011A M 60
0 20 40
Approved For Release 2003/04/18T-Ydt~k-RDP96-00787ROO0200150011-4
Figure 3.9 Distribution of Green for Machine 2
42
	12. 5M
	
	Approved For RelWse 2003/04/18 CIA-RDP96-00787ROO0200150011-4
	
	
	10. ONA
	M
	(Y)
	
	00
	7 5M
Number	M 00
o f	M
B1 ue	M 000
	M
	5. Om 000
	M
	M() 00
	M
	M 00
	2. 5jM
	MO
	M
	M
	M
	0. 0',V M
	0 20 40 60
	Figure 4.0 Distribution of Blue for Machine 2
	12. 5M
	M
	M
	MO
	M
	10. &M
	M
	M 00 00
Number	M
of	M (Y)
Red	7. 5M
	MO 000 0000
	M
	14 () (Y)
	M
	5. 01M
	M
	M
	
	
	2. 5M
	M
	M
	M
	M
	0. OIAA M M M M V M
	0 20 40 60
	
	Approved For Release 2003/04/18 : CIA-RDP96-00787ROO0200150011-4
	Figure 4.1 Distribution of Red for Machine 2
	43
Test	Description
7R
7
b
CIA-RE)P96-00
roved For Release 2003104/18
A	
AOAA49
A	
;AA44 4	Scoring		
	.
1
U1
1
pp
~	W
W%
W I j	%'%!ST'	S3	S4	S5	S6
Halstead Ca.tegory	Nonverbal test requiring abstraction of conceptual relation-	7	14	33	26	6	28
Test	ships. Score: Total errors.						
Tactual Performance	Requires placement of 10 geometrically shaped blocks in						
Test	their correct locations on a formboard while blindfolded.	16.4	11.8	7.7	7.7	11.4	6.9
	Separate RT, LT, and bimanual trials.						
	Score: Total time (min.).						
Speech Perception	Discrimination of non-word speech sounds.	4	2	0	2	5	3
Test	Score: Total errors.						
Seashore Rhythm Test	Discrimination of nonverbal rhythms. Score: Number correct.	27	25	28	29	26	29
Finger Tapping Test	Measure of finger oscillation rate for 10-sec. period, both	RT/LT	RT/LT	RT/LT	RT/LT	RT/LT	RT/LT
	RT and LT hand trials. Score: No. taps/10 sec.	53/50	53/49	48/47	54/53	47/47	48/43
Trail Making Test	Requires connecting numbered circles in order from 1 to 25.	40	16	18	19	30	27
(Part A)	Paper and pencil task. Score: Total times (sec)						
Trail Making Test	Requires connecting alphabetic and numbered circles by	56	50	55	50	54	53
(Part B)	alternating 1-A-2-B, etc. Score: Total time (sec)						
Knox Cube Test	Measure of attention span and immediate visual memory.	13	14	13	16	17	17
	Score: Number correct.						
Raven Progre ssive	Nonverbal intelligence test involving spatial matrices.	39	53	49	55	60	54
.Matrices	Score: Number correct.						
Verbal Concept	Requires abstraction of verbal conceptual relationships.	22	24	27	23	21	24
Attainment Test	Score: Number correct.						
Buschke Memory Test	Requires learning a 20-word list in a maximum of 12 trials with	Total:
14/20 17/20	
18/20	
19/20	
20/20	
20/20
	repetition of words omitted after each trial. Score: Max. no.	List:					
	words correctly remembered; List: no. words consistently remembered	8/20	14/20	11/20	16/20	15/20	16/20
						(8 trials)(7 trials',
Grooved Pegboard Test	Requires insertion of 25 pegs in their holes in a pegboard. Both	RT/LT	RT/LT	RT/LT	RT/LT	RT/LT	RT/LT
	RT and LT hand trials. Score: Total time (sec).	76/74	69/70	58/67	59/67	--*O*W	48/50
							
Spatial Relations	Requires mental rotation and identification of fipres	-	-			60	
Subtest of the PMA	errors.
rotated in 2 dimensions. Score: no. correct - no,.						
Gottscha-ldt Hidden-	I
@Requires tracing outline of simple figure hidden t4thin
~	
~	
-
v
i		
v.good	
st.
out	
outst.
Figures Test	-
1500
l
A
lines of more complexApppyod F(%ERgj~eaqquWWQ4/al&..:,CjArROP.96-00787			I