Value Added Courses

Title: Surveying and data analysis in social sciences (PU/GEOG/VACC-2/23-24)

Advertisement Date: 15/09/2023

NOTIFICATION FOR CANCELLATION

Course Type: Certificate

Commencement Date and Time: 23 ^rd November 2023 (from 5 pm to 7 pm)

(Date and Time are subject to change in exigencies.)

Date of Completion: Tentatively by the last week of January 2024

Duration of the Course: 30 (Thirty) Hours

Schedule of the Classes: 1 hour/class; 2 classes/day (From 5 pm to 7 pm); 2 days/week

Mode of Course: Offline

Medium of Instruction: English

Course Fees: 9200/- (Nine Thousand and Two Hundred only)

(Mode of Payment will be intimated subsequently to the shortlisted candidates)

Eligibility (Who can apply): Graduate in any discipline of social sciences

Course Coordinator Name: Dr. Subhajit Das

Email ID of Course Coordinator: subhajit.geog@presiuniv.ac.in

Course Objective:

The course is meant for students, researchers and academicians from different social science disciplines in general and particularly for those interested in unveiling the embedded social stories from qualitative and quantitative information. The course content intends to impart the philosophical stands of qualitative and quantitative research methodologies and the cutting-edge pragmatic approaches of surveying, data collection and analysis techniques. After completion of the course with hands-on training, the participants should have expertise in –

· Designing exclusive, quasi, and mixed methodological research framework aligned with the objectives and theorisation process

· Understanding research methods applied in social sciences and the techniques of data collection and compilation

· Carrying out interviews as a qualitative method

· Using Focus Group Discussion (FGD) and Participant Observation as qualitative research methods, encompassing the design, facilitation, data analysis and interpretation

· Collecting, analysing and interpreting narrative data with a profound understanding of human experiences, identities, and social phenomena

· Understanding the philosophical and methodological aspects of making theories grounded in data

· Practical approach to doing ethnographic research and the role of ethnography in qualitative research

· Software-based management of qualitative data for thoughtful analysis and insightful results

· Understanding the philosophy of quantification in social science

· Imparting detailed knowledge about computational techniques of modern statistical analysis.

· Identifying patterns and outliers in the data sets

· Monitoring and exploring the trends in the data

· Enhanced data processing, visualisation, and analysis to extract insightful information from big and intricate datasets

· Building robust statistical models for revealing the fundamental mechanisms that govern socio-ecological and socio-economic phenomena

Module content:

Group A: Qualitative Research:
1.	Key philosophical and methodological issues in qualitative research/inquiry.
2.	Basics of qualitative research methodology: QUAL mixed and multiple methods designing.
3.	Nature of qualitative data
4.	Data Collection: Interview- Meaning and context, designing, conduct, and ethics.
5.	Focus group discussion and participant observation.
6.	Grounded theory approach; Ethnography
7.	Interview data analysis: transcription; interpretation and theory development.
8.	Narrative Analysis in qualitative research.
9.	Application of software in qualitative analysis – Coding principles and practices, validity reliability.
Group B: Quantitative Research
10.	Introduction to quantitative surveying
11.	Sources and types of data; Tools and methods of data collection
12.	Sampling strategies and test of significance
13.	Questionnaire designing.
14.	Data analysis and visualization in SPSS.
15.	Working with real life data and visualization using Google Colab
16.	Linear Programming, Input Output Analysis.
17.	Principal Component Analysis.
18.	Global Regression analysis (non-spatial and spatial varieties).
19.	Beyond Global linear regression: applications of local regressions.
20.	Binary logistic regression.
21.	Cluster analysis - (Hierarchical and K-Medoids).

Resource Persons:

Eminent professionals from relevant fields will take the classes

General terms and conditions:

· The aspiring candidates must fill in all the mandatory fields given in the Google form within the time frame from 15 ^th September 2023 to 8 ^th October 2023 mid-night (24.00 hrs).

· Once submitted, the candidates cannot change their responses in the form.

· The application form link is –

· The selection of candidates will be done on a first-come, first-serve basis.

· The maximum number of candidates will be decided based on the availability of resources; however, the minimum number will be 15 (fifteen).

· Selected participants will be informed about the payment method subsequently via email along with their Application Number.

· On successful submission of Course fees, participants will be notified about their enrollment number and commencement details of the course.

· Once a candidate gets enrolled, the fees will be non-refundable.

Sd/-
Dr. Subhajit Das
Course Coordinators