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On An Applications of Bayes’ Rule in Probability Theory to Electrocatalytic Reaction Engineering
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Volume 4, 2017
Issue 2 (April)
Pages: 9-13   |   Vol. 4, No. 2, April 2017   |   Follow on         
Paper in PDF Downloads: 54   Since Jun. 15, 2017 Views: 1297   Since Jun. 15, 2017
Nafeesa Rehman, Department of Mathematics, Virtual University of Pakistan, Lahore, Punjab, Pakistan.
Kishwer Naheed, Department of Mathematics, Virtual University of Pakistan, Lahore, Punjab, Pakistan.
Kamran Ayub, Department of Mathematics, Riphah International University, Islamabad, Pakistan.
Qazi Mahmood Ul-Hassan, Department of Mathematics, University of Wah, Wah, Pakistan.
Bayesian methods stem from the rule of linking prior probability and conditional probability (likelihood) to posterior probability by Bayes’ rule. The posterior probability is an improved version of the prior probability of an event, through the likelihood of finding empirical evidence if the underlying assumptions (hypothesis) are valid. In the absence of a frequency distribution for the prior probability, Bayesian methods have been found more satisfactory than distribution-based techniques. The paper describes the utility of Bayes’ rule in the analysis of electrocatalytic reactor performance by means of four numerical examples involving a catalytic oxygen cathode, hydrogen evolution on a synthetic metal, the dependable of a device testing the quality of an electrocatalyst, and the range of Tafel slopes exhibited by an electrocatalyst.
Prior Probability, Posterior Probability, Conditional Probability, Mutually Exclusive Events, Mutually Exhaustive Events
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