| [[{"fid":"176","view_mode":"default","fields":{"format":"default","field_file_image_alt_text[und][0][value]":"Michael Barton","field_file_image_title_text[und][0][value]":"Michael Barton"},"type":"media","link_text":null,"attributes":{"alt":"Michael Barton","title":"Michael Barton","height":"111","width":"111","style":"color: #2a2a2a; font-family: Roboto, 'Helvetica Neue', Helvetica, Arial, sans-serif; font-size: 16px; background-color: #ffffff;","class":"panopoly-image-original media-element file-default file-responsive-image"}}]] | Michael Barton
This full day workshop is designed to provide an introduction to Cultural Consensus Analysis (CCA). CCA includes a range of quantitative tools that can be used to estimate cultural beliefs, to identify cultural “experts” in a domain of knowledge, and to identify and to test patterns of agreement and disagreement about these beliefs within and between groups.
ASU Investigators supported each semester through the ISSR seed grant initiative
Fall 2016 Seed Grant RecipientsMaking informed choices about public engagement in science and technology policyDr. Michael Bernstein, Postdoctoral Research Associate, School for the Future of Innovation in Society Hours Worked in Europe and the USDr. Alexander Bick, Assistant Professor, W. P. Carey, Economics Collaborative Research: Livelihoods in Indigenous Communities: Household Economies and Networks (LICHEN)Dr. Shauna BurnSilver, Assistant Professor, School of Human Evolution and Social Change
ISSR Fall 2016 - Winners of the Graduate Student Poster Competition!
Bring your laptop and smart phone to this hands on full day workshop, designed to introduce participants to social media data and the basic methods for collecting, filtering, and analyzing social media data using Twitter, a leading social media platform as an example. Participants will learn different ways to collect Twitter data and what data is included in each social media post or tweet including how to extract geospatial information from tweets.
Formal Methods for Qualitative Comparative Analysis (QCA)This full day workshop is designed to provide an introduction to formal methods for qualitative comparative analysis (QCA; aka configurational comparative methods). QCA includes a range of analytical tools focused on evaluating complex causal relationships in case-based comparative datasets. These methods have been used in a wide range of social science fields and provide a bridge between qualitative and quantitative approaches to formal comparison.
An Introduction to Geographically Weighted Regression
The data we measure on our environment represent the outcomes of unknown spatial processes. We typically use spatial associations between observations on different variables to infer something about these processes. One of the most common ways to do this is to formulate a linear or non-linear model linking a dependent variable, y, to set of covariates, x1, x2...xn, and to estimate the parameters of this model by regression. A potential problem with this framework is that it assumes that the parameter estimates in the model (
Non-parametric Statistical Tools for the Social SciencesSometimes researchers do not a priori have a specific model or parametric assumption in mind when modeling social science data. Nonparametric approaches are useful in these circumstances for visualization as well as for suggesting underlying assumptions for subsequent parametric models. This talk reviews the basics of nonparametric data analysis from bivariate smoothing, kernels, and splines, to full regression-style generalized additive models.
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