Hot Pixel Analysis--- 970604n

NOTE: DO NOT EDIT THIS FILE! It is generated dynamically by software.
Night/hemisphere dataset: 970604n

19 scans (in low density regions) identified for analysis:
s008 s009 s010 s011 s012 s013 s023 s024 s025 s026 s027 s028 s077 s078 s079 s080 s081 s082 s084

Procedures performed are outlined in Data Processing

Results

Figure 1---
Row 1: The sum (coadd=stack) of 19 FREX (>=4) images. The plotted numbers indicate the sum of the FREX values at each pixel. Links to the FITS images are given below the K, H and J panel.
Row 2: The plotted numbers indicate the number of scans (1-19) in which FREX>=4 was found for each hot pixel.
Below the K, H and J panel are links to the corresponding tabular data.

K H J
1) Sum of FREX Images:
Tabular Data
OR mask in Fowler's Format
FITS Image
Tabular Data
OR mask in Fowler's Format
FITS Image
Tabular Data
OR mask in Fowler's Format
FITS Image
2) Scan Counts:
k.scan_cnt.tbl
h.scan_cnt.tbl
j.scan_cnt.tbl

Figure 2---
Histograms, CDFs, and comparison statistics for K-array FREX distributions.
Row 1: Data for the coadd (stack=sum) of 19 FREX (>=4) images.
Following 19 rows: Data for each scan.
Under each CDF plot is a link to the data file, and the p-level for the two-sample KS statistic. After the histogram and CFD plot are rows listing the number of points, median, mean, p-level for the Student's t test for different means, standard deviation, p-level for the F test for different variances, and a link to the original statistics program output file.

Last update: 26-Aug-97 (7:47:38), Joe Mazzarella (mazz@ipac.caltech.edu )

	K	H	J
1) Sum of FREX Images:	Tabular Data OR mask in Fowler's Format FITS Image	Tabular Data OR mask in Fowler's Format FITS Image	Tabular Data OR mask in Fowler's Format FITS Image
2) Scan Counts:	k.scan_cnt.tbl	h.scan_cnt.tbl	j.scan_cnt.tbl

Histogram cdf data file	CDF cdf data file p(KS test)	# Points	Median Mean p(t)	Std p(F)	Statistics file
k.fex.stack.hot.tbl k.fex.stack.hot.tbl.frex-only.cdf	k.fex.stack.hot.tbl.frex-only.cdf p(KS test)=0.000000.	Npts=15	Median=15 Mean=17.9 p(t)=1.000000	Std=13.2 p(F)=1.000000	k.fex.stack.hot.tbl.frex-only.stats
k008.fex.hot.tbl k008.fex.hot.tbl.frex-only.cdf	k008.fex.hot.tbl.frex-only.cdf p(KS test)=0.000000.	Npts=2	Median=5.5 Mean=5.5 p(t)=1.000000	Std=0.707 p(F)=1.000000	k008.fex.hot.tbl.frex-only.stats
k009.fex.hot.tbl k009.fex.hot.tbl.frex-only.cdf	k009.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k009.fex.hot.tbl.frex-only.stats
k010.fex.hot.tbl k010.fex.hot.tbl.frex-only.cdf	k010.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k010.fex.hot.tbl.frex-only.stats
k011.fex.hot.tbl k011.fex.hot.tbl.frex-only.cdf	k011.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k011.fex.hot.tbl.frex-only.stats
k012.fex.hot.tbl k012.fex.hot.tbl.frex-only.cdf	k012.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k012.fex.hot.tbl.frex-only.stats
k013.fex.hot.tbl k013.fex.hot.tbl.frex-only.cdf	k013.fex.hot.tbl.frex-only.cdf p(KS test)=0.270000.	Npts=2	Median=14 Mean=14 p(t)=0.232320	Std=1.41 p(F)=0.590334	k013.fex.hot.tbl.frex-only.stats
k023.fex.hot.tbl k023.fex.hot.tbl.frex-only.cdf	k023.fex.hot.tbl.frex-only.cdf p(KS test)=0.270000.	Npts=2	Median=8 Mean=8 p(t)=0.422792	Std=1.41 p(F)=0.590334	k023.fex.hot.tbl.frex-only.stats
k024.fex.hot.tbl k024.fex.hot.tbl.frex-only.cdf	k024.fex.hot.tbl.frex-only.cdf p(KS test)=0.892778.	Npts=4	Median=6.5 Mean=6.5 p(t)=0.612398	Std=2.38 p(F)=0.428375	k024.fex.hot.tbl.frex-only.stats
k025.fex.hot.tbl k025.fex.hot.tbl.frex-only.cdf	k025.fex.hot.tbl.frex-only.cdf p(KS test)=0.270000.	Npts=2	Median=4 Mean=4 p(t)=0.367308	Std=0 p(F)=0.000000	k025.fex.hot.tbl.frex-only.stats
k026.fex.hot.tbl k026.fex.hot.tbl.frex-only.cdf	k026.fex.hot.tbl.frex-only.cdf p(KS test)=0.270000.	Npts=2	Median=4 Mean=4 p(t)=0.367308	Std=0 p(F)=0.000000	k026.fex.hot.tbl.frex-only.stats
k027.fex.hot.tbl k027.fex.hot.tbl.frex-only.cdf	k027.fex.hot.tbl.frex-only.cdf p(KS test)=0.963945.	Npts=2	Median=6 Mean=6 p(t)=0.778880	Std=1.41 p(F)=0.590334	k027.fex.hot.tbl.frex-only.stats
k028.fex.hot.tbl k028.fex.hot.tbl.frex-only.cdf	k028.fex.hot.tbl.frex-only.cdf p(KS test)=0.963945.	Npts=2	Median=8.5 Mean=8.5 p(t)=0.697732	Std=6.36 p(F)=0.140893	k028.fex.hot.tbl.frex-only.stats
k077.fex.hot.tbl k077.fex.hot.tbl.frex-only.cdf	k077.fex.hot.tbl.frex-only.cdf p(KS test)=0.441306.	Npts=4	Median=11 Mean=11.8 p(t)=0.358718	Std=6.29 p(F)=0.164775	k077.fex.hot.tbl.frex-only.stats
k078.fex.hot.tbl k078.fex.hot.tbl.frex-only.cdf	k078.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k078.fex.hot.tbl.frex-only.stats
k079.fex.hot.tbl k079.fex.hot.tbl.frex-only.cdf	k079.fex.hot.tbl.frex-only.cdf p(KS test)=0.270000.	Npts=2	Median=4 Mean=4 p(t)=0.367308	Std=0 p(F)=0.000000	k079.fex.hot.tbl.frex-only.stats
k080.fex.hot.tbl k080.fex.hot.tbl.frex-only.cdf	k080.fex.hot.tbl.frex-only.cdf p(KS test)=	Npts=	Median= Mean= p(t)=	Std= p(F)=	k080.fex.hot.tbl.frex-only.stats
k081.fex.hot.tbl k081.fex.hot.tbl.frex-only.cdf	k081.fex.hot.tbl.frex-only.cdf p(KS test)=0.963945.	Npts=2	Median=5.5 Mean=5.5 p(t)=1.000000	Std=2.12 p(F)=0.409665	k081.fex.hot.tbl.frex-only.stats
k082.fex.hot.tbl k082.fex.hot.tbl.frex-only.cdf	k082.fex.hot.tbl.frex-only.cdf p(KS test)=0.181300.	Npts=3	Median=9 Mean=11.3 p(t)=0.417741	Std=5.86 p(F)=0.170046	k082.fex.hot.tbl.frex-only.stats
k084.fex.hot.tbl k084.fex.hot.tbl.frex-only.cdf	k084.fex.hot.tbl.frex-only.cdf p(KS test)=0.660386.	Npts=3	Median=7 Mean=7 p(t)=0.510219	Std=2 p(F)=0.485071	k084.fex.hot.tbl.frex-only.stats