| YGARB.com | Yaakov Garb |
This course is about the analysis of quantitative data and the methods through which reliable quantitative data can be created. It gives a solid yet largely non-mathematical introduction to statistics and research design useful in both the life and social sciences, and hands-on experience in using these. The course emphasizes exploration and discovery—often through data visualization—as key aspects of quantitative analysis. It will give students the skills and confidence to independently create and analyze data that matters to them, and hopes to convey the excitement of data sleuthing, and an appreciation of the rigor and elegance of principled data analysis and presentation. The course provides a solid footing in the descriptive analysis of univariate and bivariate data; literacy in the basics of statistical inference, the analysis of variance, and regression; and an intuitive overview of a menu of multivariate approaches, including some advanced yet intuitively accessible approaches not commonly covered in an introductory statistics course. Students will also learn about and practice some of the methods through which reliable and relevant quantitative data is obtained: experiments in controlled and naturalistic settings, bureaucratic data, and survey and sampling techniques, including questionnaire design. The goal is for students to gain sufficient orientation and experience to be able to design and conduct their own basic quantitative analysis, but also, to know the limits of their knowledge, the techniques that lie beyond these, and how to seek the expert advice and training needed for more refined analysis. The course revolves around a core textbook (De Veaux et al, 2005), supplementary readings and datasets, and (SAS) JMP 5--powerful yet accessible software that supports intuitive, interactive visual data discovery.
Students in the course can obtain a detailed syllabus and course materials from the instructor.