Statistical data analysis is critical in Pharmacology. In case a pharmacy organization intends to perform trials on various patients in line with a new drug to help fight a disease, the number of patients expected to participate in the activity is expected to be over 500 hence the need for statistical analysis (Walker & Whittlesea, 2012). Additionally, in case the company needs to launch a new variant of drugs, there is a need to carry a survey and arrive at some meaningful conclusion. This means that statistical data is used for decision making in Pharmaceuticals. With the dynamic nature of pharmacology, statistical data can assist make substantive decisions that can help develop Pharmaceutical organizations (Vogel, Mass & Gebauer, 2010). Furthermore, in case important marketing decisions are to be made, data analysis is required.
The appropriate published literature in Pharmaceuticals includes scholar articles, dissertations, various conference proceedings and other technical reports (Lutz & Kenakin, 2011). Literally, research often informs a story while the existing literature narrates past stories relating to the research topic and helps provide new perspectives in various sectors including pharmacology. Some papers that include statistical analysis include Warholak et al. (2014), Ndlovu & Smelter (2005) and Pang & Lu (2016).
Primary sources include publications that report on pharmaceutical statistics and may be in the form of conference papers, thesis, and dissertation, monographic series or journal articles (Smith, 2010). The various works often present new results and link them with an existing knowledge base. Secondary evidence includes publications published in the literature and often generalizes, interpret and otherwise add value to the original information. The tertiary sources of information in data analysis and presentation seeks to compile both primary and secondary providing a broader overview of the study topic (Dodge et al., 2001). This includes the reference nature of publications like encyclopedias, handbooks and various databases such as Drug Facts and Micromedex.
Some papers that include statistical analysis include:
Warholak, T. L., Hilgaertner, J. W., Dean, J. L., Taylor, A. M., Hines, L. E., Hurwitz, J., ... & Malone, D. C. (2014). Evaluation of an educational program on deciphering heterogeneity for medical coverage decisions. Journal of Managed Care Pharmacy, 20(6), 566-573.
Ndlovu, I. M., & Smelter, M. A. (2005). The Use of Analytical Method Validation to Compare Results Obtained Using Boreal Laser HF Analyse and Isokinetic Sampling Technique. In Test and Measurement Conference.
Pang, M. H., & Lu, Z. H. (2016). Clinical study on the efficacy of iodine-131 in combined with Fufangjiakang tablets in the treatment of Graves disease. Journal of Hainan Medical University, 22(12), 98-100.
References
Dodge, Y., Rao, C. R., & International Conference on Recent Developments in Statistical Data Analysis and Inference. (2001). Statistical data analysis and inference. Amsterdam: North-Holland.
Lutz, M. W., & Kenakin, T. P. (2011). Quantitative molecular pharmacology and informatics in drug discovery. Chichester, England [u.a.: Wiley.
Smith, F. (2010). Conducting your pharmacy practice research project: A step-by-step guide. London: Pharmaceutical.
Vogel, H. G., Mass, J., & Gebauer, A. (2010). Drug discovery and evaluation. Berlin: Springer.
Walker, R., & Whittlesea, C. (2012). Clinical pharmacy and therapeutics. Edinburgh: Churchill Livingstone.
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