This book is about doing variation analysis. My goal is to give you a manual which will take you through a variationist analysis from beginning to end. Although I will cover the major issues, I will not attempt a full treatment of the theoretical issues nor of the statistical underpinnings. Instead, you will be directed to references where the relevant points are treated fully and in detail. In later chapters, explicit discussion will be made as to how different types of analysis either challenge, contribute to, or advance theoretical issues.

What do you do with your data once you have collected it? This chapter will elucidate the procedures for judicious handling of a large body of natural speech materials, such as audio files, interview reports, and consent forms.

How do I visualise my results so I can understand my data better? This chapter will outline several methods for turning all the numbers from statistical modelling into plots. I will include basic cosmetics for conditional inference trees and random forests, effects plots for glmer models, and a few enhancements you can make using ggplot functions, including cow plots and ribbon plots.

How do I report my results? This chapter will outline the method for reporting the results of statistical modelling, including rate (%), number of observations (Ns/cell) for each level of a categorical independent variable, and Total Number of observations (Total N) in the data.

How do you conduct a sociolinguistic interview? How do you talk to strangers, your targeted sample of individuals who you do not know yet? This chapter will discuss ways and means of mitigating the observer’s paradox, enabling the analyst to obtain natural speech data.

How do I conduct a mixed effects logistic regression of a linguistic variable?This chapter will illustrate the procedures for performing statistical modelling using mixed effects logistic regression with the lme4 package in R. It will review the steps for conducting analyses, for finding the best model for the feature under study, and what to do with it when you find it.

How do you find a linguistic variable? This chapter will discuss the key construct in the variationist paradigm – the linguistic variable. It will detail its definition, describe what a linguistic variable is, how to identify it, and how to circumscribe it.

What do you do with a linguistic variable once you’ve found one?

This chapter will provide a step-by-step procedure for setting up an analysis of a linguistic variable. It will detail the procedures for coding, how to illustrate the linguistic variable and how to test claims about one variant over another.

This chapter will cover new techniques beyond probing empirical data for data exploration. It will show you how to use a conditional inference tree (ctree) and random forest (cforest) to understand complex data interactions, pinpoint difficulties in research design, and discover data anomalies.The focus will be on techniques for resolving data and linguistic problems in preparation for statistical modelling

This chapter focuses on statistical modelling and asks, first, why we should use statistical modelling of linguistic variables. It will cover the terms ‘factor weight’, ‘p-value’, ‘coefficient’, ‘sum coding’, ‘treatment coding’ and describe what they mean.

This chapter will provide a step-by-step procedure for setting up an analysis of a linguistic variable. It will detail the procedures for coding, how to illustrate the linguistic variable, and how to test claims about one variant over another.

How do you collect data? This chapter will outline tried-and-true data collection techniques for conducting fieldwork in the speech community.