Mahbubul Majumder

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Lineups [4, 28] have been established as tools for visual testing similar to standard statistical inference tests, allowing us to evaluate the validity of graphical findings in an objective manner. In simulation studies [12] lineups have been shown as being efficient: the power of visual tests is comparable to classical tests while being much less stringent(More)
Statistical graphics play a crucial role in exploratory data analysis, model checking and diagnosis. Until recently there were no formal visual methods in place for determining statistical significance of findings. This changed, when Buja et al. (2009) conceptually introduced two protocols for formal tests of visual findings. In this paper we take this a(More)
In soybean [Glycine max (L.) Merr.], iron deficiency results in interveinal chlorosis and decreased photosynthetic capacity, leading to stunting and yield loss. In this study, gene expression analyses investigated the role of soybean replication protein A (RPA) subunits during iron stress. Nine RPA homologs were significantly differentially expressed in(More)
Graphics play a crucial role in statistical analysis and data mining. This paper describes developments to assist the use of graphics for making inferential statements. It examines the lineup protocol described in Buja et al. [2009] developing numerical statistics to measure the quality of the lineup. Distance measures are developed that describe how close(More)
Mobile learning, also known as m-learning, is a convenient, means of delivering informational content to learners using current mobile technology devices. Nowadays, most of the learners have a smart phone that support video as well as have fast internet connection. They are using native content as well as web content for learning purpose. These learning(More)
Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. Computational approaches such as network analysis are important tools to understand system dynamics as well as to identify critical components that could be further explored as therapeutic targets. Here, we performed perturbation analysis of a(More)
Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models.(More)
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