Statistics : a concise mathematical introduction for students, scientists, and engineers / David W. Scott.

Includes bibliographical references and index.

Data analysis and understanding -- Classical probability -- Random variables and models derived from classical probability and postulates -- Bivariate random variables, transformations, and simulations -- Approximations and asymptotics -- Parameter estimation -- Hypothesis testing -- Confidence intervals and other hypothesis tests -- Topics in statistics.

"The field of statistics has a rich history that has become tightly integrated into the emerging field of data sciences. Collaboration with computer scientists, numerical analysts, and decision makers characterizes the field. The role of statistics and statisticians is to find actionable information in a noisy collection of data. Every field of academic endeavor encounters this problem: from the electrical engineer trying to find a signal in a noisy channel to an English professor trying to determine the authorship of a contested newly discovered manuscript. There are two basic tasks for the statistician. First is to characterize the distribution of possible outcomes using a batch of representative data. An actuary may be asked to find a dollar loss for car accidents that is not exceeded 99.999% of the time. An economist may be asked to provide useful summaries of a collection of income data. The histogram is our primary tool here, an idea that did not appear until the 17th century; see Graunt (1662)."-- Provided by publisher.