Basic data summarization is a statistical technique that involves summarizing data sets into simpler forms. Data summarization is an essential step in data analysis, and it helps in understanding and interpreting the data. To provide an overview of the data set and make informed decisions, one must identify key insights, trends, patterns, and relationships within the data set.

The most commonly used techniques for data summarization include measures of central tendency, measures of variability, measures of shape of the distribution, measures of location, and graphical representation. Measures of central tendency include the mean, median, and mode, which provide a measure of the central value of the data set. Measures of variability include the range, variance, and standard deviation. These measures provide insight into the spread of the data set.

Quartiles, deciles, and percentiles are statistical measures that divide a dataset into groups or intervals based on their position in the distribution.  Graphs such as histograms, box plots, scatter plots, and line charts provide a visual representation of the data set. Among them, Box Whisker plots provide a visual representation of the range, median, and quartiles of the data set.

In conclusion, basic data summarization is an essential technique in data analysis, and it provides a simplified overview of the data set.