# Mumbai Massacre Torahcode Experiments

On this webpage, we show the network of Torah code tables that resulted from
our experiments as described previously. Each table must have one key word
for each of the topic categories: *What* and * Where *, plus key words from three
of other the remaining four categories:
*Who*, *When Date*, *When Year* and *How*.

## When Date Year How

We show the first three most statistically significant tables that resulted from this category
of experiments. These tables are all in the same place and with a core of the same key words and
ELSs. However, from one table to the other, you will find one key word change, making all
these 3 tables especially related.

The search produced a cylinder size of 74. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 9.5/10,000.

The search produced a cylinder size of 73. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 15.5/10,000.

The search produced a cylinder size of 74. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 18.5/10,000.

## Who When Date Year

### Taj Mahal

There was no table for the Taj Mahal with p-value less than 1/50.

### Oberoi

The search produced a cylinder size of 73. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 154.5/10,000.

### Nariman

The search produced a cylinder size of 74. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 5.5/10,000.

## Who When Date How

### Taj Mahal

There was no statistically signficant table for the Who When Date How category involving the Taj Mahal.

### Oberoi

The search produced a cylinder size of 78. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 22.5/10,000.

### Chabad

Right:

Left: The search produced a cylinder size of 2541. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 7.5/10,000.

## Who When Year How

### Taj Mahal

In this category, there is a large table with the key word Taj Mahal. Because of its
size we do not show it. The p-value for the table is 48.5/10,000.

### Oberoi

The search produced a cylinder size of 262. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is less than 85.5/10,000.

### Chabad House

In this category, there are tables for both Chabad House and Nariman. The first table
occurs with the key word Mumbai. Not shown is a similar table with the key word Bombay
and where the p-value is 9.5/10,000.

The search produced a cylinder size of 152. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is less than 24.5/100,000.

The search produced a cylinder size of 77. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is less than 26.5/10,000.

## Who When Date Year How

### Taj Mahal

There was no statistically signficant table for the Who When Date How category involving the Taj Mahal.

### Oberoi

The search produced a cylinder size of 73. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is less than 37.5/10,000.

### Nariman

There was a table of 163 rows by 111 column on a cylinder size of 951 with ELSs of the key words
טבח טרר,
*Massacre Terror*;
מומביי, *Mumbai*;
הודו, *India*;
נארימן,
*Nariman*;
בכט חשון, *On Cheshvon 29*;
בהתשסט *in 5769*; and
מחבלים
*Terrorists*. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text is 3.5/10,000. Because the table
is 163 rows by 111 columns, it is too large to show so we omit the table.

## Developments

The search produced a cylinder size of 153. With expected number of ELSs set to 100,
the probability that a text from the ELS random placement text population would produce
a table as compact as that produced by the Torah text would be less than 1/10,000,
had the key word choices been a priori.

Finding by Dr. Moshe Katz with additions by Rabbi Glazerson and Professor Haralick

The search produced a cylinder size of 300. The expected number of ELSs was set to 100.

Finding by Rabbi Glazerson