The histogram and boxplot are effective and simple graphical tools, which are broadly used to explore the characteristics of the distribution of univariate data. In this proposed work, two versions of a statistical plot, called a sample variance plot (SV-plot), are defined which illustrate squared deviations from the sample variance formula. These plots capture symmetry and skewness of the distribution analogous to a histogram. Also, they detect outliers in the data with reference to two novel bounds introduced on each plot analogous to a boxplot. Further, one version of the SV-plot is employed to display hypothesis testing for a single population mean, and for a difference between two population means. Finally, the performance of the SV-plot is compared with histogram and boxplot using actual and simulated data sets. It is seen that the SV-plot has additional benefits beyond identifying characteristics of the distribution.