diff --git a/README.md b/README.md
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@@ -78,7 +78,7 @@ Tue, Feb 27 | [Questionnaire design and multi-item scales](pages/feb27-surveys-p
 Thu, Feb 29 | [Experimental design](pages/feb29-causal-relationships.md) | [slides](slides/13-experiments-pt1.pdf)
 ~~Tue, Mar 5~~ | ~~Spring break, no class~~ |
 ~~Thu, Mar 7~~ | ~~Spring break, no class~~ |
-Tue, Mar 12 | Experimental design (part III) | 
+Tue, Mar 12 | [Example experimental papers](pages/mar12-experiments-examples.md) | [slides](slides/14-experiments-pt2.pdf)
 Thu, Mar 14 | Intro to regression modeling | 
 Tue, Mar 19 | Diagnostics, factors, std coefficients | 
 Thu, Mar 21 | Simpson’s paradox, exemplar papers, in-class activity | 
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 This lecture is the first part of a series on designing experiments. We discussed what it means for something to be a "cause" or an "effect," the three ingredients needed for establishing a causal relationship, and how experiments as a research method match the characteristics of causal relationships very well.
 
-We also discussed within-vs-between subjects designs and their trade-offs.
+We also discussed within-vs-between subjects designs and their trade-offs, as well as Latin Squares and counterbalancing.
 
 
 ### Lecture Readings
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+## L14: Experimental Design Part II - Examples ([pdf](../slides/14-experiments-pt2.pdf), [video]())
+
+[![Lecture14-Experiments2](../assets/images/14-experiments-pt2.jpg)](../slides/14-experiments-pt2.pdf)
+
+This lecture is the second part of a series on designing experiments. 
+
+We discussed and critiqued examples of studies using experiments, including a true (randomized) experiment in the Tomkins et al study of double blind reviewing at the Conference on Web Search and Data Mining.
+
+
+### Lecture Readings
+
+> Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Wadsworth Publishing.
+
+The discussion of cause as an *inus condition* -- "insufficient but nonredundant part of an unnecessary but sufficient condition" -- follows Chapter 1 from the book (Experiments and generalized causal inference).
+
+---
+
+> Tomkins, A., Zhang, M., & Heavlin, W. D. (2017). [Single versus double blind reviewing at WSDM 2017](https://arxiv.org/pdf/1702.00502). arXiv preprint arXiv:1702.00502
+
+A nice example of a randomized experiment carried out to assess the impact of single vs double-blind reviewing of conference papers. The paper reports that: 
+- “Reviewers in the single-blind condition [...] preferentially bid for papers from top universities and companies.”
+- “Single-blind reviewers are significantly more likely than their double-blind counterparts to recommend for acceptance papers from famous authors [odds multiplier 1.64], top universities [1.58], and top companies [2.10].”
+
+
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