  One of the major task of wireless sensor network is to sense accurate data
from the physical environment. Hence in this paper, we develop an estimated
data accuracy model for randomly deployed sensor nodes which can sense more
accurate data from the physical environment. We compare our results with other
information accuracy models and shows that our estimated data accuracy model
performs better than the other models. Moreover we simulate our estimated data
accuracy model under such situation when some of the sensor nodes become
malicious due to extreme physical environment. Finally using our estimated data
accuracy model we construct a probabilistic approach for selecting an optimal
set of sensor nodes from the randomly deployed maximal set of sensor nodes in
the network.
