The capacity to forecast earthquakes is extremely beneficial, especially in high-risk seismic zones, yet exact predictions remain difficult. One possible explanation is the insufficient incorporation of statistical techniques into earthquake research. In this work, I used exploratory data analysis (EDA), a data-driven parametric statistical approach, to look at earthquake records from Japan, utilizing data given by the Japan Meteorological Agency. The intervals between earthquakes closely matched an exponential distribution, given by a single parameter, λ, indicating occurrence frequency. Unlike the standard Gutenberg-Richter law, earthquake magnitudes follow a normal distribution with two parameters: µ (mean) and σ (scale). After creating these distributions and their parameters, considerable changes became apparent.