Kirjahaku

This text offers a challenge to critics informed by new theories about the essential indeterminacy of language and hence literature. Nevertheless, post-structuralist methodologies have played an increasingly important part in studies of "Emma" during the last 20 years. This collection brings together the most significant of these studies and, by means of the editor's introduction and context notes, helps the reader to assess the extent to which a revolution in critical practice has changed the understanding of Austen's classic novel.

A fun romp through one man's life's events with a quirky look at what he learned. The facts are pretty comedic and irreverent to the extent that he was constantly being lectured or dressed down for expressing his off the cuff opinion. You know that filter we're supposed to have that prevents us from saying really dumb things? Apparently, the author's filter is broken.

Jane Austen's novels are loved because they possess a comedic power that is often conveyed through the singular voice of the narrators. Film adaptations, however, have often been unsatisfactory because they lack or awkwardly render features, particularly the voice of the narrators. This work argues for a fresh approach that begins with a reading of the novels that emphasizes their auditory and visual dimensions. Building on their examination of Austen's inherently cinematic features, the authors then develop productive new readings of the films. Instructors considering this book for use in a course may request an examination copy here.

We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.

We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.