Seminar Presentation and Viva voce

Paper Code: 
MTM 228
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

Course Objectives:

This course will enable the students to –

  1. Create awareness in students about current trends, issues and researches
  2. Expose students to case studies /capstone project and enable them to prepare a report based on primary/secondary data

 

Course Outcomes:

Course

Course outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

MTM 228

Seminar Presentation and Viva Voce

CO 78Awareness of current trends, issues and researches.

CO 79Apply Descriptive statistics and machine learning using statistical tools SPSS/ Orange.

CO 80Prepare a report based on primary or secondary data.

Approach in teaching:

Lab class, regular interaction with Supervisor

Learning activities for the students:

SPSS exercises, Orange exercises ,Presentations

Viva and Presentation
 

 

15.00
Unit I: 
UNIT I

Multivariate Analysis of Variance (MNOVA)-Testing assumptions of MNOVA, Running MNOVA with SPSS, Multiple comparisons in MNOVA, Output from MNOVA

Regression- Simple Linear Model, Linear Model with several Predictors, Model estimation, Assessing Goodness of Fit, R and R square, Assessing individual Predictors

Bias in Regression Model- Unusual cases, Generalizing the Model, Sample size in Regression, Assumptions, What if assumptions are violated

Interpreting Regression Model –Descriptive, Summary of Model, Model Parameters, Excluded variables, Assessing Multicollinearity,

 

15.00
Unit II: 
UNIT II

Moderation and mediation of variables

Exploratory Factor Analysis-Discovering Factors, Running the analysis, Interpreting output from SPSS, Reliability Analysis, How to report Factor analysis.

Logistic Regression- Background to logistic regression, Principles behind logistic regression, Binary Logistic Regression, Interpreting logistic regression, How to report logistic regression, Testing assumptions, Predicting several categories.

Essential Readings: 

Apart from the 30 hrs. lab sessions, students are required to devote 2 hrs. per week under the supervision of their respective supervisors on regular basis for guidance on report.

 

 

Suggested Readings:

  • IBM SPSS Statistics 20 Core System User’s Guide
  • IBM SPSS Modeler 18.0 User's Guide
  • G N  Prabhakara, Synopsis Dissertation And Research To Pg Students, Jaypee Brothers Medical Publishers; second edition (2016)

 

Academic Year: 
2020-2021
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