Introduction to Experimental Syntax Methods

This is a first course in experimental syntax. The goal is to teach students how to think about syntactic data like an experimentalist. The course will be a combination of nuts-and-bolts tutorials, high-level conceptual discussions, and hands-on experience. When the course is over, students should be well-prepared to design, deploy, and analyze their own acceptability judgment experiments, and to extend that knowledge to other experimental methods in linguistics and psycholinguistics. Students should also be well-prepared to engage in cutting-edge debates about what (formal) experimental evidence can tell us about syntactic theory.

This course will work best if you bring a laptop with you to the class so that you can work along with the slides and discussion.

We are going to use Excel and R extensively in this course, so you should have them installed on your computer. Here are some links:

Schedule and Materials

Here is a link to the full set of lecture slides for the course: - last updated 12.14.18. These basically form a textbook (in slide format) for the design and analysis of acceptability judgment experiments (over 300 slides).

All assignments are due before the start of class the following week

class topic data files scripts assignments
1 Sections 1 & 2: Introduction and Conditions exercise 1
2 Section 3: Items exercise 2
3 Section 4: Ordering items full example experiment exercise 3
exercise 4
4 Section 5: Judgment tasks Sprouse 2011 no exercise
5 Section 6: Recruiting participants AMT templates exercise 5
6 Section 7: Pre-processing item keys
raw AMT data
long format no items
long format with items
long format no outliers
convert to long format v1
convert to long format v2
add items, conditions, factors
add z-scores v1
add z-scores v2
putting all scripts together
identify outliers
exercise 6
exercise 7
7 Section 8: Plotting long format no outliers distribution plots
interaction plots
means and medians
normal distribution
parameters and statistics
exercise 8
data for 8
8 Section 9: Building linear mixed-effects models long format no outliers linear mixed-effects models
interaction plot with points
subject and item differences
9 Section 10: Fisher, F, and p long format no outliers randomization tests
bootstrap tests
the F distribution
10 Section 11: Neyman-Pearson long format no outliers the alpha level
multiple comparisons
11 Section 12: Bayesian statistics and Bayes factors the monty hall problem
12 Validity and replicability of judgments papers to download
13 Spillover?

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