Recall that data are broadly classified into quantitative data and qualitative data. Quantitative data represent the measurements or counts of numerical values, such as varying heights of students in a class. Conversely, qualitative data, also known as categorical data, represent non-numerical variables such as the different colors of hair. For efficient statistical analysis, these unorganized, large data sets are summarized and represented numerically in tabular form or visually in graphical form. For example, the temperature changes measured during a day can be summarized in the form of a table. These data can also be represented graphically. Here, the time is given along the horizontal axis, and the temperature is displayed along the vertical axis. The points in the graph are joined to form the pattern providing a visual understanding of how the daytime temperature changes with time. The graph also identifies the outliers from the other data values that indicate extreme temperatures observed in the day.