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This article is about the Bayesian modelling of the parameters of a simple linear regression with normal errors. It studies the use of non-informative normal priors to the regression parameters. It has an application on modelling gluten content in terms of protein content of a variety of wheat. The exact estimations of credible sets of the regression parameters obtained from real and simulated data by using MCMC. The posterior estimates of the gluten content in terms of protein content are better in this regression model with normal non-informative prior. Journal of Institute of Science and Technology, 2014, 19(1): 121-128

Bayesian Modelling by Method of Normal Regression: A Case of Modelling Gluten Content in terms of Protein Content in a Variety of Wheat