Prashantt492: Creating course page via bot

2026-03-04T10:10:00Z

Creating course page via bot

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{{Infobox Course
| code = HSL722
| name = Data Analysis for Behavioral Research using R
| credits = 4
| credit_structure = 3-0-2
| pre_requisites = HSL721
| overlaps =
}}

== HSL722 : Data Analysis for Behavioral Research using R ==
PG students. The course will comprise of 4 broad themes. In the 1st part of the course, we will introduce the basics of R. R syntax and its libraries will be extensively used for other parts of the course. In the 2nd part, we will introduce basics of statistics that are needed for understanding ideas of frequentist-based hypothesis testing methods. This will include understanding t-test, linear regressions and basics of linear-mixed models. HSL723 Advanced Computational Methods 1.5 Credits (0.5-0-2) We will first introduce the students to the basics of computational modeling. We will discuss examples of computational models and the question of what can be learnt. Students will be introduced to two learning algorithms: decision trees and logistic regression. They will learn about validation of their models, both internally and externally. During the course practical, they will get the opportunity to train their own computational models to solve a simple problem. HSL724 Advanced Experimental Methods 1.5 Credits (0.5-0-2) We will first summarize the basics of experimentation. Following this, we will focus on a particular experimental paradigm (e.g., Eye-tracking, EEG) where the key concepts related to the paradigm will be discussed. Some research papers that have used this paradigm in domains such as attention, language processing, etc. will be discussed. Advantages and challenges to the paradigm will be discussed. In addition, practical sessions will be conducted to get a hands-on experience on a particular paradigm. HSL725 Advanced Qualitative Methods 1.5 Credits (0.5-0-2) We will start by discussing the qualitative research paradigm, noting the ontological and epistemological assumptions and values of reflexivity and subjectivity. We then learn about planning and designing qualitative research and consider the sampling requirements and ethical concerns. Various data collection techniques will be introduced, such as interviews, focus group, textual data: surveys, diaries, secondary sources. Finally, we will learn to analyze the qualitative data, focusing on three different approaches - thematic analysis, discourse analysis, and interpretative phenomenological analysis. Teamwork and interactive exercises will be emphasized. Students will gain hands-on experience in various qualitative methods and analysis techniques. Students will also be introduced to NVivo – a widely used qualitative analysis software.

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Prashantt492: Creating course page via bot