This Specialization covers the use of statistical methods in today's business, industrial, and social environments, including several new methods and applications. H.G. Wells foresaw an era when the understanding of basic statistics would be as important for citizenship as the ability to read and write. Modern Statistics for Data-Driven Decision-Making teaches the basics of working with and interpreting data, skills necessary to succeed in Wells’s “new great complex world” that we now inhabit.
This specialization is intended for individuals that work in the general field of data science and analytics. Learners may have job titles related to data science specialist, data science managers, statisticians, and engineers. This specialization would also appeal to market researchers, individuals involved in product development and those that work in the area of online testing.
Learners pursuing this course should have excitement for solving problems with data and applying what they learn on a project.
Applied Learning Project
Learners will select an existing set of data for evaluation and analysis using methods and formulas presented in each course of the specialization. The mini-project will be submitted in four parts, one submission for each course in the specialization. By the end, each learner will have chosen a problem to focus on, developed ideas about how to approach it, determined appropriate methods to tackle it, and performed data analysis to generate insight and inform solutions. The project will be peer reviewed using a grading rubric as a guide.
