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Peter
Gwozdz |
Results: |
#NOME? |
SBP
= Statistical Background Percent |
13 |
End
of the Gap |
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15,0% |
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#NOME? |
minimum
from this column |
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Poisson
Confidence Interval (Demonstration) |
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Confidence
Calculation |
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#NOME? |
Statistical Mountain
Number |
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#NOME? |
Mountain Number |
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Poisson tail |
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#NOME? |
minimum from this column |
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| 70% |
Confidence (70% is
recommended) |
#NOME? |
Statistical (Mountain)
Background |
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#NOME? |
Gap Number |
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12 |
Cutoff integer check of
user input |
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for use in the Poisson
function |
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#NOME? |
minimum SBP value from
this column |
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4 |
Number of samples; must be an integer |
40 |
Number of samples in the
set; must be an integer |
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| 12 |
Cutoff |
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12 |
Cutoff |
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#NOME? |
Type Outliers |
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2 |
Gap check |
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80% |
Enter the confidence |
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90,0% |
Probability |
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| 2 |
Gap |
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2 |
Gap |
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#NOME? |
(Mountain) Background |
10 |
Gap display check |
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#NOME? |
Confidence Interval
Lower Number |
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| 10 |
Gap frequency display |
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Click sheet "SPD Doc" for instuctions |
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= Average Gap Frequency |
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Statistical |
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#NOME? |
Calculated Low Confidence
Limit |
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#NOME? |
Confidence Interval
Upper Number |
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To reduce the x-axis on the graph |
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#NOME? |
Statistical Gap Number |
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SBP Trials |
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End = End of Gap = Cutoff
+ Gap -1 |
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Gap |
Gap |
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#NOME? |
Calculated High
Confidence Limit |
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Delete cells at the bottom;
all 5 of these columns |
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#NOME? |
Statistical Average Gap
Frequency |
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Cutoff |
Gap |
Cutoff |
Gap |
End |
Mountain |
M+G |
Gap |
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Statistical Numbers |
Average |
Average |
SBP |
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This column finds the
recommended cutoff |
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Do not delete the rows, just highlight the data & press
Delete |
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= Statistical Background |
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Number |
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Number |
Mountain |
Gap |
Frequency |
Frequency |
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I downloaded the Poisson
functions from: |
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This column finds the
recommended gap |
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Step |
Total |
Frequency |
Gap |
Display |
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#NOME? |
Size (of the Type) |
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12 |
2 |
13 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
This is the requested
Cutoff & Gap |
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http://statpages.org/confint.html |
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#NOME? |
#NOME? |
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0 |
#NOME? |
#NOME? |
0 |
0 |
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#NOME? |
Size confidence minimum |
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11 |
1 |
11 |
1 |
11 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
These blue rows are the
"neighbor" values |
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These Poisson functions
are Macros |
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#NOME? |
#NOME? |
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1 |
#NOME? |
#NOME? |
1 |
0 |
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#NOME? |
Size confidence maximum |
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11 |
2 |
11 |
2 |
12 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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Cutoff / Gap with +/- One |
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So Excel gives a warning
when opening this file |
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#NOME? |
#NOME? |
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2 |
#NOME? |
#NOME? |
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0 |
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11 |
3 |
11 |
3 |
13 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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There may be duplicates
in here |
|
Peter Gwozdz |
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#NOME? |
#NOME? |
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3 |
#NOME? |
#NOME? |
3 |
0 |
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12 |
1 |
12 |
1 |
12 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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See if your values are
"local minimums" |
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#NOME? |
#NOME? |
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4 |
#NOME? |
#NOME? |
4 |
0 |
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12 |
3 |
12 |
3 |
14 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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5 |
#NOME? |
#NOME? |
5 |
0 |
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13 |
1 |
13 |
1 |
13 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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6 |
#NOME? |
#NOME? |
6 |
0 |
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13 |
2 |
13 |
2 |
14 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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7 |
#NOME? |
#NOME? |
7 |
0 |
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13 |
3 |
13 |
3 |
15 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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8 |
#NOME? |
#NOME? |
8 |
0 |
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10 |
0 |
10 |
1 |
10 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
The rest of these are 2
counts beyond your values |
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#NOME? |
#NOME? |
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9 |
#NOME? |
#NOME? |
9 |
0 |
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10 |
1 |
10 |
1 |
10 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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There may be "false
minimums" at another gap beyond your gap |
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#NOME? |
#NOME? |
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10 |
#NOME? |
#NOME? |
10 |
0 |
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10 |
2 |
10 |
2 |
11 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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And duplicates |
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#NOME? |
#NOME? |
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11 |
#NOME? |
#NOME? |
11,9 |
0 |
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10 |
3 |
10 |
3 |
12 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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12 |
#NOME? |
#NOME? |
12 |
10 |
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10 |
4 |
10 |
4 |
13 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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13 |
#NOME? |
#NOME? |
13 |
10 |
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11 |
0 |
11 |
1 |
11 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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14 |
#NOME? |
#NOME? |
13,1 |
0 |
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11 |
4 |
11 |
4 |
14 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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15 |
#NOME? |
#NOME? |
15 |
0 |
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12 |
0 |
12 |
1 |
12 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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16 |
#NOME? |
#NOME? |
16 |
0 |
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12 |
4 |
12 |
4 |
15 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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17 |
#NOME? |
#NOME? |
17 |
0 |
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13 |
0 |
13 |
1 |
13 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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18 |
#NOME? |
#NOME? |
18 |
0 |
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13 |
4 |
13 |
4 |
16 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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19 |
#NOME? |
#NOME? |
19 |
0 |
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14 |
0 |
14 |
1 |
14 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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20 |
#NOME? |
#NOME? |
20 |
0 |
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14 |
1 |
14 |
1 |
14 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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21 |
#NOME? |
#NOME? |
21 |
0 |
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14 |
2 |
14 |
2 |
15 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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22 |
#NOME? |
#NOME? |
22 |
0 |
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14 |
3 |
14 |
3 |
16 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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23 |
#NOME? |
#NOME? |
23 |
0 |
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14 |
4 |
14 |
4 |
17 |
#NOME? |
#### |
###### |
#NOME? |
##### |
#NOME? |
#NOME? |
#NOME? |
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#NOME? |
#NOME? |
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24 |
#NOME? |
#NOME? |
24 |
0 |
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25 |
#NOME? |
#NOME? |
25 |
0 |
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