Indiana University Bloomington

Every Year

Statistics S501
Statistical Methods I: Introduction To Statistics

Class Time: 9:30-10:45
Class Days: Tu, Th
Capacity: 25
Pre-Requisites: One undergraduate course in statistics
Algebra Required: concepts
Calculus Required: no
Recommended follow-up classes: S503
Syllabus: No Syllabus Avaliable
Keywords: linear regression; continuous outcomes; least squares
Description: This course takes a systematic approach to the exposition of the general linear model for continuous dependent variables, including correlation, simple linear and multiple regression. Students are introduced to the use of statistical analysis software. This course is broken up into three sections. The first section covers fundamental concepts of quantitative data analysis: including measurement and presentation and an introduction to the notion used throughout the semester. The second section focuses on the assumptions and mechanics of the classical linear regression model. At the end of the second section you will have a good mechanical knowledge of regression analysis. The third section includes a practical exposition of the general linear model as we begin to relax the assumptions of the classical linear regression model. At the end of the third section you will have a deeper theoretical and applied understanding of the flexibility and limitations of the general linear regression model for social science data. At the end of this course students will be able to think creatively about the use of statistical methods in their own research.
Substantive Orientation: Social sciences; non-experimental
Applied/Theoretical: applied
How Software is Used: data analysis
Problem Sets: yes
Data Analysis: yes, as part of assignments
Presentation: informal presentations
Exams: quizzes
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