Dear all, 

We are glad to announce the publication of "Statistical Modeling for (Actual) 
Hypothesis Testing: Building Cumulative Knowledge in Corpus Linguistics" by 
Tove Larsson and Gregory R. Hancock in the Cambridge Elements in Corpus 
Linguistics series. It is freely downloadable until 11 August, using the 
following URL: 
https://www.cambridge.org/core/elements/statistical-modeling-for-actual-hypothesis-testing/E0CEF5D438391940EFC92AB8916686D6

Here is a summary of the Element:
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.

Best wishes, 

Paul Baker & Gaëtanelle Gilquin (series editors)

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