Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data This textbook provides a straightforward introduction to the statistical analysis of language Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data

Analyzing linguistic data : a practical introduction to statistics using R

Redundancy and reduction: Speakers manage syntactic information density

http://pact.cs.cmu.edu/pubs/KLI-KoedingerCorbettPerfetti2012-pre.pdf

The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning.

More than words: Frequency effects for multi-word phrases

Corpus linguistics is one of the fastest-growing methodologies in contemporary linguistics. In a conversational format, this article answers a few questions that corpus linguists regularly face from linguists who have not used corpus-based methods so far. It discusses some of the central assumptions (‘formal distributional differences reflect functional differences’), notions (corpora, representativity and balancedness, markup and annotation), and methods of corpus linguistics (frequency lists, concordances, collocations), and discusses a few ways in which the discipline still needs to mature. At a recent LSA meeting … [with an obvious bow to Frederick Newmeyer] Question: So, I hear you’re a corpus linguist. Interesting, I get to see more and more

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1749-818X.2009.00149.x

What is Corpus Linguistics

Theoretical linguists have traditionally relied on linguistic intuitions such as grammaticality judgments for their data. But the massive growth of computer-readable texts and recordings, the availability of cheaper, more powerful computers and software, and the development of new probabilistic models for language have now made the spontaneous useoflanguageinnaturalsettingsarichandeasilyaccessiblealternativesourceofdata. Surprisingly, many linguists believe that such ‘usage data’ are irrelevant to the theory of grammar. Four problems are repeatedly brought up in the critiques of usage data: 1. Correlated factors seeming to support reductive theories; 2. Pooled data invalidating grammatical inference; 3. Syntactic choices reducing to lexical biases; and 4. Cross-corpus differences undermining corpus studies. Presenting a case study of work on the English dative alternation, we show first,that linguistic intuitions of grammaticality are deeply flawed and seriously underestimate the space of grammatical possibility, and second, that the four problems in the critique of usage data are empirical issues that can be resolved by using modern statistical theory and modeling strategies widely used in other fields. The new models allow linguistic theory to solve more difficult problems than it has in the past, and to build convergent projects with psychology, computer science, and allied fields of cognitive science.

/pdf/predicting-the-dative-alternation-1icnuaypul.pdf

Anna Cueni

Papers

Predicting the dative alternation