This thesis focuses on various frequency plots and their application in representing the big data sets. The research of this works aimed to find out which frequency plots can be used for best representing the data. For this purpose, some background research was done in the field of visualizations primarily about frequency plots. Before an actual study took place - a pilot study was done with 5 participants to verify the hypothesis and research questions. Eye tracker was used during the study to track the eye movement of the participants. It is also important to see which parts of the visualizations are more critical. In other words, what are areas of focus when the frequency plot is shown to the users? The reason for using the eye tracker is to determine the cognitive load of the participant; Cognitive load helps the analyst to understand if one kind of task or plot type was more stressful for the users than the others. The actual study conducted with 24 participants who performed various tasks on different frequency plots and their result was analyzed. The plots scales taken for this study were both linear and root. During the analysis, the comparison was made both between the linear and root scaled version of Dot plots, histograms, polylines and also within the plots type of the same scale. The data for the eye tracker was collected, but results are not discussed in this thesis.