In this paper, the distribution of absolute value of a normal random variable is deliberated under Bayesian structure. This distribution is also known as Half-normal distribution (HND). The posterior distributions of the parameter of HND are derived using non-informative priors which are uniform and Jeffreys priors. The properties of posterior distributions are discussed via simulation and real data set. The graphs of the posterior distribution are presented with real data set. Bayes estimates are obtained using the loss functions (Squared error loss function, Modified loss function, Quadratic loss function and Degroot loss function). Interval estimates are constructed through credible intervals. Bayesian hypothesis testing using both priors is also presented in this study.