## Analyzing Linguistic Data: A Practical Introduction to Statistics using RStatistical 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. |

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### Contents

Preface x | 1 |

Graphical data exploration | 20 |

Probability distributions | 44 |

Basic statistical methods | 68 |

ofcovariance | 108 |

Clustering and classiﬁcation | 118 |

Regression modeling | 165 |

Mixed models | 241 |

347 | |

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afﬁxes AgeSubject animacy AnimacyOfRec animate inanimate anova axis binomial distribution Bismarck Archipelago bootstrap boxplot Brown corpus chi-squared classiﬁcation cluster coefﬁcients column conﬁdence interval corpus correlation counts curve data frame data points data set deﬁned degrees of freedom density dependent variable deviance Dutch Error t value Estimate Std factor ﬁle ﬁnd ﬁrst ﬁt ﬁtted function InflectionalEntropy input interaction Intercept latencies LengthInLetters levels lists logistic regression matrix meanFamiliarity mixed-effects model nonlinear normal distribution NVratio observed obtained outliers p-value package panel of Figure parameters plot poetry poetry poetry Poisson Poisson distribution predicted predictors principal components analysis probability proportions prose poetry prose prose prose quantiles R-squared random effects random numbers random variable ratings RealizationOfRec regression line regression model residuals right panel sample scatterplot signiﬁcant slope speciﬁes standard deviation statistical subjects subset summary synsets t-test tag trigrams variance vector verbs word frequency WrittenFrequency xlab xtabs ylab zero zijn

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Page 342 - Morphological Influences on the Recognition of Monosyllabic Monomorphemic Words. Journal of Memory and Language, 53:496512,2006.