The purpose of conducting an experiment is to generate data. This data can be analyzed to see if the experimenter's hypothesis was correct and can be accepted or incorrect and rejected. Data that can be precisely counted or measured is known as quantitative data. Data that is more descriptive is called qualitative data. If a data table measures the growth of a plant, on days one through fifteen, each day the height is measured in centimeters, will be adding to the quantitative data. However, if the experimenter notices a trend, for instance, the plant seemed to be growing rapidly between days ten and fifteen, this is an example of qualitative data. If one says, the plant seems taller, more robust, greener--these are more examples of qualitative data.