It’s no wonder that statisticians feel threatened by data scientists. Statisticians deal with nebulous concepts like point estimates, margins of error, confidence intervals, standard errors, p-values, hypothesis testing, and the proverbial argument between the ‘frequentists’ and ‘Bayesians.’
Data scientists on the other hand, closely follow the ‘data science process’; data ingest, data transformation, exploratory data analysis, model selection, model evaluation, and data storytelling. Many more people can embrace data science. -reference
Statistics was primarily developed to help people deal with pre-computer data problems like testing the impact of fertilizer in agriculture, or figuring out the accuracy of an estimate from a small sample. Data science emphasizes the data problems of the 21st Century, like accessing information from large databases, writing code to manipulate data, and visualizing data. reference
Note: We have many other degrees that are analytical (e.g., economics, statistics, physics). The degrees listed are the interdisciplinary degrees.