Statistical modeling for (actual) hypothesis testing : building cumulative knowledge in corpus linguistics / Tove Larsson, Gregory R. Hancock

Format:

Book

Author/Creator:

Larsson, Tove, author.

Hancock, Gregory R., author.

Series:

Cambridge elements. Elements in corpus linguistics

Cambridge elements. Elements in corpus linguistics, 2632-8097

Language:

English

Subjects (All):

Corpora (Linguistics)--Statistical methods.

Corpora (Linguistics).

Statistical hypothesis testing.

Physical Description:

1 online resource

Place of Publication:

Cambridge : Cambridge University Press, 2026

Summary:

"By building knowledge in a deliberate and systematic manner, we can gain a more complete understanding of a given research area relevant to corpus linguists. Specifically, empirically informed hypotheses (i.e., hypotheses that result from a synthesis of findings from all relevant prior studies) play a key role in this endeavor in that they enable us to test to what extent generalizations from previous research are consistent with our results, or if we need to make adjustments to our existing knowledge or theory. In this Element, we aim to provide a practical and accessible introduction to select statistical methods for evaluating such empirically informed hypotheses. In particular, we illustrate techniques from the broader null-hypothesis significance testing framework (e.g., equivalence testing), and structural equation modeling framework (e.g., measured variable path analysis), with the goal of encouraging knowledge building in a more principled and systematic manner in corpus linguistics"-- Cambridge Core

Contents:

Introduction and definition of key concepts

Cumulative knowledge accrual and theory building : the role of empirically informed hypotheses

Testing informed directional hypotheses

Testing informed hypotheses of nonzero mean differences

Testing informed hypotheses of similarity using equivalence testing

Testing informed hypotheses of similarity using mean and covariance structure models

Testing informed hypotheses of specific relations among variables

Summing up and looking ahead

Notes:

Online resource; title from PDF title page (Cambridge Core, viewed July 29, 2026)

Other Format:

Print version: Larsson, Tove Statistical modeling for (actual) hypothesis testing

ISBN:

9781009660907

100966090X

9781009660877

100966087X

OCLC:

1592116360

Publisher Number:

CIPO000409190

Access Restriction:

Restricted for use by site license