Statistical Evaluations for
Public Experiment #9
Here are three test procedures that evaluate
the remoteviewing session with the target data. All of these
tests utilize Farsight's Session
Analysis Machine (SAM). Click on the test names to get an
explanation of each test.
The analyses below are for:
Viewer: Courtney Brown
Session: Session #2
TEST
#1: Comparing the Remoteviewing session Data with the Target
Attributes (Click for explanation)
The session data are: 
Session/Target Matches: 
surface: surface 
match 
surface: level topology 

land: land 
match 
land: manmade 

land: level topology 

water: water 

water: land/water interface 

atmospherics: smoke or burning (natural or manmade) 

surface structure(s): surface structure(s) 

surface structure(s): one 

surface structure(s): multiple 

surface structure(s): city 

structure(s) materials: manmade materials 

structure(s) general location: on land 

structure(s) general location: on a flat surface 

subject(s): subject(s) 
match 
subject(s): male 
match 
subject(s): female 

subject(s): one/few 
match 
subject(s): many/crowd 

light: bright 
match 
environment: urban 

activity: activity or movement by subject(s) 

sounds: talking, shouting, voices 
match 
sounds: booming or roaring 

sounds: loud 

temperatures: cold 
match 
dominant session elements: structure(s) on a surface 

sketches: structure(s) 

sketches: structure(s) on a surface 

sketches: subject(s) 
match 
sketches: horizontal base surface 

sketches: extensive water 

The target attributes not perceived are:
Missed Target Attributes: 
surface: irregular topology 
land: natural 
land: irregular topology 
land: steep peaks 
water: ice or snow 
atmospherics: natural smells 
natural object(s): natural object(s) 
natural object(s): on a surface 
mountain: mountain(s) 
mountain: one 
mountain: multiple 
environment: natural 
environment: harsh natural 
sounds: windtype sounds 
dominant session elements: natural environment 
sketches: natural object on a surface 
sketches: subject(s) on an outside base surface 
sketches: sloping or peaking base surface(s) 
The total matches between the session and the target are: 9
The total number of target attributes not perceived: 18
The total number of session entries is: 33
The total number of target entries is: 27
A. The total matches between the session and the target as a
proportion of the total number of target attributes are: 0.333
B. The total matches between the session and the target as a
proportion of the total number of session entries are: 0.273
General session/target correspondence (the average of A and B
above): 0.303
The normal chisquare value with 1 degree of freedom testing
the fit of the session to the target based on the table below
is: 0.077
The alternative chisquare value with 1 degree of freedom based
on only the distribution of chosen session attributes (the top
row of the table below) is: 0.050
The correlation between this session's data and the target attributes
is: NEGATIVE
NOTE: The chisquare value does not take into account the direction
of the relationship between the session data and target attributes.
The chisquare value is a useful measure ONLY if there is a positive
correlation between the target's attributes and the session's
SAM entries. (That is, there needs to be a reasonably high number
of target and session matches.)

Target 0: 
Target 1: 
Session 1: 
24 
9 
Session 0: 
42 
18 
Chisquare Values: 
Significance Level: 
3.84 
0.05 
5.02 
0.025 
6.63 
0.010 
7.88 
0.005 
10.8 
0.001 
INTERPRETATION OF THE CHISQUARE STATISTIC
1. If the value of the chisquare statistic is equal to or greater
than the chisquare value for a desired significance level in
the table above, and if the correlation between the session data
and the target attributes is positive, then the session's data
are statistically significant descriptors of the target.
2. If the value of the chisquare statistic is less than the
chisquare value for a desired significance level, then the remoteviewing data for the session are not statistically significant.
This normally means that there are decoding errors in the data.
3. If the value of the chisquare statistic is equal to or greater
than the chisquare value for a desired significance level but
the correlation between the session data and target attributes
is negative, then the session either has major decoding errors,
or there may be consciousmind intervention and/or invention
in the data gathering process.
HEURISTIC COMPARISON: Comparing the Session with a Target with
Randomly Chosen Attributes
The total matches between the session and a target with randomly
chosen attributes are: 7
The total number of session data entries is: 33
The total number of target attribute entries is: 27
The total matches between the session and the target as a proportion
of the total number of target entries are: 0.259
The total matches between the session and the target as a proportion
of the total number of session entries are: 0.212
The normal chisquare value with 1 degree of freedom testing
the fit of the session to the target based on the table below
is: 1.518
The alternative chisquare value with 1 degree of freedom based
on only the distribution of chosen session attributes is: 0.979
TEST
#2: THE RUSSELL PROCEDURE (Click for explanation)
Part I.
The expected mean number of chance matches for this session is:
9.581
The standard deviation (hypergeometric distribution) for this
mean is: 2.106
The 90% confidence interval for this is: [6.117, 13.045]
The 95% confidence interval for this is: [5.453, 13.708]
The 98% confidence interval for this is: [4.685, 14.477]
The unweighted (actual) number of matches between the session
and the target are: 9
The weighted number of matches between the session and the target
are: 9.298
INTERPRETATION: If the unweighted and/or weighted number of matches
between the session and the target are outside of (that is, greater
than) the desired confidence interval, then the number of matches
obtained in the session was not by chance.
Part II.
IF THE SESSION DATA WERE RANDOM, HOW MANY SAM ENTRIES WOULD BE
NEEDED TO DESCRIBE THE TARGET AS COMPLETELY AS IS DONE BY THE
ACTUAL SESSION?
From 1000 Monte Carlo samples:
The mean number of random session pseudo SAM entries that are
needed to achieve 9 matches with the target is: 30.567
The standard deviation is: 7.151
Lowest number of pseudo attributes from sample = 13
Highest number of pseudo attributes from sample = 58
The 90% confidence interval for this is: [18.803, 42.331]
The 95% confidence interval for this is: [16.551, 44.583]
The 98% confidence interval for this is: [13.941, 47.193]
Compare these intervals with the actual number of session entries:
33
INTERPRETATION: If the actual number of session SAM entries is
outside of (that is, less than) the desired confidence interval,
then the number of entries utilized by the remote viewer
to obtain the number of matches between the session and the target
was not by chance.
TEST
#3: CORRESPONDENCE and CORRELATION (Click for explanation)
PART I.
The correspondence data in the table immediately below are computed
using the targets from the public demonstration only. The "Session/Target"
correspondence numbers are calculated between the remoteviewing session for this experiment and all of the targets used in the
public demonstration. The "Target/Target" correspondence
numbers are calculated between the real target for this experiment
and all of the other targets in the public demonstration pool.
Experiment
Number: 
Session/Target
Correspondence: 
Target/Target
Correspondence: 
Experiment #1 
0.503 
0.219 
Experiment #3 
0.758 
0.303 
Experiment #4 
0.622 
0.365 
Experiment #5 
0.785 
0.243 
Experiment #6 
0.793 
0.285 
Experiment #7 
0.793 
0.276 
Experiment #8 
0.659 
0.288 
Experiment #9 
0.303 
1.0 
Experiment #10 
0.732 
0.281 
Experiment #11 
0.608 
0.279 
Experiment #12 
0.352 
0.821 
Experiment #14 
0.727 
0.580 
Experiment #15 
0.857 
0.271 
The correlation coefficient is: 0.707 with an N of 13
INTERPRETATION: All targets have a variety of descriptive characteristics.
When comparing one target with another, both similarities and differences
will be found between the two. The correspondence numbers are one measure
of the degree of similarity between any two sets of SAM data, and these
numbers can be used to compare one target with another target, or a remoteviewing session with a target. The closer a remoteviewing session is to
describing all of a target's characteristics, the higher will be the correspondence
number between the session and the target. Since a pool of targets normally
contains targets with a great variety of descriptive characteristics, comparing
correspondence numbers for the remoteviewing session and its target across
a variety of other targets tests how closely the session describes all of
the essential characteristics of its real target. When compared with other
targets with many different characteristics, both the remoteviewing session
and its real target should have correspondence numbers that vary similarly.
The correlation coefficient summarizes this relationship. The correlation
coefficient can vary between 1 and 1. The closer its value is to 1, the
more closely the remoteviewing session describes its real target's various
characteristics.
PART II.
The correlation coefficient is computed as in Part I above, but
now using a large (240) pool of SAM targets.
The correlation coefficient is: 0.723 with
an N of 240
The lowest correspondence number for the session and pool is:
0.117
The highest correspondence number for the session and pool is:
0.836
The lowest correspondence number for the target and pool is:
0.218
The highest correspondence number for the target and pool is:
0.889
INTERPRETATION: Similarly as with Part I above. The closer the
value of the correlation coefficient is to 1, the more closely
the remoteviewing session describes its real target's various
characteristics.
