  Quantum computers promise to surpass the most powerful classical
supercomputers when it comes to solving many critically important practical
problems, such as pharmaceutical and fertilizer design, supply chain and
traffic optimization, or optimization for machine learning tasks. Because
quantum computers function fundamentally differently from classical computers,
the emergence of quantum computing technology will lead to a new evolutionary
branch of statistical and data analytics methodologies. This review provides an
introduction to quantum computing designed to be accessible to statisticians
and data scientists, aiming to equip them with an overarching framework of
quantum computing, the basic language and building blocks of quantum
algorithms, and an overview of existing quantum applications in statistics and
data analysis. Our goal is to enable statisticians and data scientists to
follow quantum computing literature relevant to their fields, to collaborate
with quantum algorithm designers, and, ultimately, to bring forth the next
generation of statistical and data analytics tools.
