The discussion centers around the integral of the Inverse Gamma Distribution's probability density function (pdf) and its implications. It confirms that the integral of the pdf equals 1, validating it as a proper distribution. The conversation then shifts to calculating probabilities for a random variable following the Inverse Gamma Distribution, specifically for values greater than or less than a constant. A method is proposed for finding the cumulative distribution function (cdf) by relating it to the Gamma distribution, as the cdf of the Inverse Gamma does not have a closed form. The participants exchange ideas on the validity and approach of these calculations.