# Statistics for Linguistics with R [electronic resource] : a Practical Introduction.

##### By: Gries, Stefan Thomas

Material type: TextSeries: Mouton textbook: Publisher: Berlin : De Gruyter, 2013Edition: 2nd edDescription: 1 online resource (374 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9783110307474; 3110307472Subject(s): Linguistics -- Statistical methods | R (Computer program language) | LANGUAGE ARTS & DISCIPLINES -- Linguistics -- Historical & Comparative | Linguistics -- Statistical methods | R (Computer program language)Genre/Form: Electronic books.Additional physical formats: Print version:: Statistics for Linguistics with R : A Practical Introduction.DDC classification: 410.285/5362 LOC classification: P138.5 | .G75 2013Online resources: Click here to access onlineItem type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Preface; Chapter 1. Some fundamentals of empirical research; 1. Introduction; 2. On the relevance of quantitative methods in linguistics; 3. The design and the logic of quantitative studies; 3.1. Scouting; 3.2. Hypotheses and operationalization; 3.2.1. Scientific hypotheses in text form; 3.2.2. Operationalizing your variables; 3.2.3. Scientific hypotheses in statistical/mathematical form; 3.3. Data collection and storage; 3.4. The decision; 3.4.1. One-tailed p-values from discrete probability distributions; 3.4.2. Two-tailed p-values from discrete probability distributions.

3.4.3. Extension: continuous probability distributions4. The design of a factorial experiment: introduction; 5. The design of a factorial experiment: another example; Chapter 2. Fundamentals of R; 1. Introduction and installation; 2. Functions and arguments; 3. Vectors; 3.1. Generating vectors; 3.2. Loading and saving vectors; 3.3. Editing vectors; 4. Factors; 4.1. Generating factors; 4.2. Loading and saving factors; 4.3. Editing factors; 5. Data frames; 5.1. Generating data frames; 5.2. Loading and saving data frames; 5.3. Editing data frame s; 6. Some programming: conditionals and loops.

6.1. Conditional expressions6.2. Loops; 7. Writing your own little functions; Chapter 3. Descriptive statistics; 1. Univariate statistics; 1.1. Frequency data; 1.1.1. Scatterplots and line plots; 1.1.2. Pie charts; 1.1.3. Bar plots; 1.1.4. Pareto-charts; 1.1.5. Histograms; 1.1.6 Empirical cumulative distributions; 1.2. Measures of central tendency; 1.2.1. The mode; 1.2.2. The median; 1.2.3. The arithmetic mean; 1.2.4. The geometric mean; 1.3. Measures of dispersion; 1.3.1. Relative entropy; 1.3.2. The range; 1.3.3. Quantiles and quartiles; 1.3.4. The average deviation.

1.3.5. The standard deviation/variance1.3.6. The variation coefficient; 1.3.7. Summary functions; 1.3.8. The standard error; 1.4. Centering and standardization (z-scores); 1.5. Confidence intervals; 1.5.1. Confidence intervals of arithmetic means; 1.5.2. Confidence intervals of percentages; 2. Bivariate statistics; 2.1. Frequencies and crosstabulation; 2.1.1. Bar plots and mosaic plots; 2.1.2. Spineplots; 2.1.3. Line plots; 2.2. Means; 2.2.1. Boxplots; 2.2.2. Interaction plots; 2.3. Coefficients of correlation and linear regression; Chapter 4. Analytical statistics.

1. Distributions and frequencies1.1. Distribution fitting; 1.1.1. One dep. variable (ratio-scaled); 1.1.2. One dep. variable (nominal/categorical); 1.2. Tests for differences/independence; 1.2.1. One dep. variable (ordinal/interval/ratio scaled) and one indep. variable (nominal) (indep. samples); 1.2.2. One dep. variable (nom./cat.) and one indep. variable (nom./cat.) (indep.samples); 1.2.3. One dep. variable (nom./cat.) (dep. samples); 2. Dispersions; 2.1. Goodness-of-fit test for one dep. variable (ratio-scaled); 2.2. One dep. variable (ratio-scaled) and one indep. variable (nom.); 3. Means.

3.1. Goodness-of-fit tests.

This book is the revised and extended second edition of Statistics for Linguistics with R. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, and a revision of overview sections on statistical tests and regression modeling. The main revision is a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-

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