Path: news.mathworks.com!not-for-mail
From: <HIDDEN>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Histogram and Normality test
Date: Wed, 6 Aug 2008 23:41:02 +0000 (UTC)
Organization: University of Memphis
Lines: 24
Message-ID: <g7dcqe$38k$1@fred.mathworks.com>
References: <g7cmca$a2c$1@fred.mathworks.com>
Reply-To: <HIDDEN>
NNTP-Posting-Host: webapp-02-blr.mathworks.com
Content-Type: text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding: 8bit
X-Trace: fred.mathworks.com 1218066062 3348 172.30.248.37 (6 Aug 2008 23:41:02 GMT)
X-Complaints-To: news@mathworks.com
NNTP-Posting-Date: Wed, 6 Aug 2008 23:41:02 +0000 (UTC)
X-Newsreader: MATLAB Central Newsreader 233092
Xref: news.mathworks.com comp.soft-sys.matlab:484087



"Mastaneh " <mtorkama@iupui.edu> wrote in message
<g7cmca$a2c$1@fred.mathworks.com>...
> Dear all,
> 
> I have a 2^18-length data, sampled at 48 kHz with a 16-bit 
> ADC. The histogram is very close to the normal 
> distribution, but the data always fails the normality 
> hypothesis tests. 
> When plotting the histogram with 1000 bins, there are 
> various spikes in the figure. I know reducing the number of 
> bins help get a smoother curve, but am I correct in 
> assuming that these spikes are the reason the tests fail? I 
> mean, the test needs to average the spike amplitudes to get 
> the estimated distribution, so the result doesn't have the 
> same moments as the original sample. 


I would investigate the source of the spikes in the original
data and not in the histogram bins.  There are some scripts
to remove outliers and this may be all you need. 
> 
> Thanks for any explanation,
> Mastaneh