Descriptive Statistics is the type of statistics that provides enough data that quantitatively describe certain features or characteristics of the data set. These statistics summarize information by listing certain measures of the aimed dataset so that it becomes easier to describe their necessary features.
Graphs can be one of the greatest tools to graphically make sense of quantitative data and so it is often used to summarize certain datasets.
Basic Categories Under Descriptive Statistics
Descriptive Statistics often describe some characteristics by measuring or analyzing certain datasets. So, depending on what they measure these statistics are categorized into two basic types and they are -
- Measures of central tendency (describes the center)
- Measures of variability (describes the dispersion within)
For example, one may be tasked with gathering ratings of the stress level of college students in the medical science faculty. If 0 signifies “not stressed at all” and 10 stands for “extremely stressed” and the dataset shows ratings of all 50 students in their second year.
Descriptive statistics would help determine the average stress level among the students (central tendency) and/or the spread of their anxiety level (variability measures) since if everybody’s stress level is over 5, that would require separate attention.
Use of the Term in Sentences
- Descriptive statistics are often used on sample datasets to determine the characteristics of a larger population.