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  2. EDU S052

Intermediate and Advanced Statistical Methods for Applied Educational Research
EDU S052

Course Information

Description

This course is designed for those who want to extend their data analytic skills beyond a basic knowledge of multiple regression analysis and practice communicating their findings clearly to audiences of researchers, practitioners, and policymakers. S-052 contributes directly to the diverse data analytic toolkit that the well-equipped empirical researcher must possess to perform sensible analyses of complex educational, psychological, and social data. The course begins by reviewing multivariate linear regression and continues with program evaluation, multilevel modeling, measurement, multivariate methods, and generalized linear models. Specific techniques covered include regression discontinuity, difference-in-differences, fixed and random effects modeling, reliability estimation, and principal components analysis. S-052 is an applied course. It offers conceptual explanations of statistical techniques and provides many opportunities to implement and interpret statistical analysis, including through statistical coding in either R or Stata.
 
Prerequisites: Successful completion of S-040 or equivalent course covering applied regression analysis through multivariate regression and interaction terms.

School Graduate School of Education
Credits 4
Cross Reg

Available for Harvard Cross Registration

Department Education
Course Component Regular Course
Instruction Mode In Person
Subject Education
Grading Basis HGSE Student Option (Letter Graded, Sat/Unsat)
Learning Goals The course is designed to develop and extend the data analytic skills acquired in earlier courses and to help students learn to communicate findings clearly to audiences of other empirical researchers, scholars, policymakers, practitioners, students, and parents. We have designed S-052 to contribute to the diverse data analytic toolkit that you will need to perform sensible and believable analyses of complex educational, psychological, and social data.
Career Focus <p>This course supports careers that require data analytic literacy and data analytic fluency. Literacy goals include asking critical questions of current educational, social science, and health science research reports and peer-reviewed publications. Fluency goals include productive contribution to quantitative research teams and written analyses. Common next steps include doctoral research trajectories, research and policy think tanks, governmental organizations, data journalism, and the wide array of for-profit and not-for-profit organizations that value data analytic skills.</p>