言語学における量的研究法<br>Quantitative Methods in Linguistics

個数:
電子版価格
¥9,380
  • 電子版あり

言語学における量的研究法
Quantitative Methods in Linguistics

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合は、ご注文数量が揃ってからまとめて発送いたします。
    3. 美品のご指定は承りかねます。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 277 p.
  • 言語 ENG
  • 商品コード 9781405144254
  • DDC分類 401.21

基本説明

Includes sample datasets contributed by researchers working in a variety of sub-disciplines of linguistics; uses R, the statistical software package most commonly used by linguists, to discover patterns in quantitative data and to test linguistic hypotheses; includes student-friendly end-of-chapter assignments and is accompanied by online resources.

Full Description

Quantitative Methods in Linguistics offers a practical introduction to statistics and quantitative analysis with data sets drawn from the field and coverage of phonetics, psycholinguistics, sociolinguistics, historical linguistics, and syntax, as well as probability distribution and quantitative methods.



Provides balanced treatment of the practical aspects of handling quantitative linguistic data
Includes sample datasets contributed by researchers working in a variety of sub-disciplines of linguistics
Uses R, the statistical software package most commonly used by linguists, to discover patterns in quantitative data and to test linguistic hypotheses
Includes student-friendly end-of-chapter assignments and is accompanied by online resources at available in the 'Downloads' section, below

Contents

Acknowledgments. Design of the Book.

1. Fundamentals of Quantitative Analysis.

1.1 What We Accomplish in Quantitative Analysis.

1.2 How to Describe an Observation.

1.3 Frequency Distributions: A Fundamental Building Block of Quantitative Analysis.

1.4 Types of Distributions.

1.5 Is Normal Data, Well, Normal?.

1.6 Measures of Central Tendency.

1.7 Measures of Dispersion.

1.8 Standard Deviation of the Normal Distribution.

Exercises.

2. Patterns and Tests.

2.1 Sampling.

2.2 Data.

2.3 Hypothesis Testing.

2.3.1 The Central Limit Theorem.

2.3.2 Score Keeping.

2.3.3 H0: µ = 100.

2.3.4 Type I and Type II Error.

2.4 Correlation.

2.4.1 Covariance and Correlation.

2.4.2 The Regression Line.

2.4.3 Amount of Variance Accounted For.

Exercises.

3. Phonetics.

3.1 Comparing Mean Values.

3.1.1 Cherokee Voice Onset Time: µ1971=µ2001.

3.1.2 Samples Have Equal Variance.

3.1.3 If the Samples Do Not Have Equal Variance.

3.1.4 Paired t Test: Are Men Different from Women?.

3.1.5 The Sign Test.

3.2 Predicting the Back of the Tongue from the Front: Multiple Regression.

3.2.1 The Covariance Matrix.

3.2.2 More than One slope: The bi.

3.2.3 Selecting a Model.

3.3 Tongue Shape Factors: Principal Components Analysis.

Exercises.

4. Psycholinguistics.

4.1 Analysis of Variance: One Factor, More than Two Levels.

4.2 Two Factors: Interaction.

4.3 Repeated Measures.

4.3.1 An Example of Repeated Measures ANOVA.

4.3.2 Repeated Measures ANOVA with a Between-Subjects Factor.

4.4 The "Language as Fixed Effect" Fallacy.

4.5 Exercises.

5. Sociolinguistics.

5.1 When the Data are Counts - Contingency Tables.

5.1.1 Frequency in a Contingency Table.

5.2 Working with Probabilities: The Binomial Distribution.

5.2.1 Bush or Kerry?.

5.3 An Aside about Maximum Likelihood Estimation.

5.4 Logistic Regression.

5.5 An Example from the [∫]treets of Columbus.

5.5.1 On the Relationship between x2 and G2.

5.5.2 More than One Predictor.

5.6 Logistic Regression as Regression: An Ordinal Effect - Age.

5.7 Varbrul/R Comparison.

Exercises.

6. Historical Linguistics.

6.1 Cladistics: Where Linguistics and Evolutionary Biology Meet.

6.2 Clustering on the Basis of Shared Vocabulary.

6.3 Cladistic Analysis: Combining Character-Based Subtrees.

6.4 Clustering on the Basis of Spelling Similarity.

6.5 Multidimensional Scaling: A Language Similarity Space.

Exercises.

7. Syntax.

7.1 Measuring Sentence Acceptability.

7.2 A Psychogrammatical Law?.

7.3 Linear Mixed Effects in the Syntactic Expression of Agents in English.

7.3.1 Linear Regression: Overall, and Separately by Verbs.

7.3.2 Fitting a Linear Mixed-Effects Model: Fixed and Random Effects.

7.3.3 Fitting Five More Mixed-Effects Models: Finding the Best Model.

7.4 Predicting the Dative Alternation: Logistic Modeling of Syntactic Corpora Data.

7.4.1 Logistic Model of Dative Alternation.

7.4.2 Evaluating the Fit of the Model.

7.4.3 Adding a Random Factor: Mixed Effects Logistic Regression.

Exercises.

Appendix 7A.

References.

Index

最近チェックした商品