Statistical properties of the scrape-off layer (SOL) plasma fluctuations are
studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first
time, plasma fluctuations as well as parameters that describe the fluctuations
are compared across measurements from a mirror Langmuir probe (MLP) and from
gas-puff imaging (GPI) that sample the same plasma discharge. This comparison
is complemented by an analysis of line emission time-series data, synthesized
from the MLP electron density and temperature measurements. The fluctuations
observed by the MLP and GPI typically display relative fluctuation amplitudes
of order unity together with positively skewed and flattened probability
density functions. Such data time series are well described by an established
stochastic framework which model the data as a superposition of uncorrelated,
two-sided exponential pulses. The most important parameter of the process is
the intermittency parameter, {\gamma} = {\tau}d / {\tau}w where {\tau}d denotes
the duration time of a single pulse and {\tau}w gives the average waiting time
between consecutive pulses. Here we show, using a new deconvolution method,
that these parameters can be consistently estimated from different statistics
of the data. We also show that the statistical properties of the data sampled
by the MLP and GPI diagnostic are very similar. Finally, a comparison of the
GPI signal to the synthetic line-emission time series suggests that the
measured emission intensity can not be explained solely by a simplified model
which neglects neutral particle dynamics
