IS4071 Data Analytics Syllabus:

IS4071 Data Analytics Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES:

1. Recognize the importance of data analytics
2. Exhibit competence on data analytics packages
3. Apply solution methodologies for industrial problems.

UNIT I INTRODUCTION

Introduction to Multivariate Statistics-Degree of Relationship among Variables-Review of Univariate and Bivariate Statistics-Screening Data Prior to Analysis-Missing Data, Outliers, Normality, Linearity, and Homoscedasticity.

UNIT II MULTIPLE REGRESSION

Multiple Regression- Linear and Nonlinear techniques- Backward-Forward-Stepwise Hierarchical regression-Testing interactions (2way interaction) – Analysis of Variance and Covariance (ANOVA & ANCOVA) – Multivariate Analysis of Variance and Covariance (MANOVA & MANCOVA).

UNIT III LOGISTIC REGRESSION

Regression with binary dependent variable -Simple Discriminant Analysis Multiple Discriminant analysis-Assessing classification accuracy- Conjoint analysis (Full profile method).

UNIT IV PRINCIPAL COMPONENT ANALYSIS

Principal Component Analysis -Factor Analysis- Orthogonal and Oblique Rotation-Factor Score Estimation-Multidimensional Scaling-Perceptual Map-Cluster Analysis (Hierarchical Vs Nonhierarchical Clustering).

UNIT V

Latent Variable Models an Introduction to Factor, Path, and Structural Equation Analysis- Time series data analysis (ARIMA model) – Decision tree analysis (CHAID, CART) – Introduction to Big Data Management.

COURSE OUTCOMES:

On completion of the course, the student will be able to:
 To recognize the importance of data analytics
 To Exhibit competence on data analytics packages
 To apply solution methodologies for industrial problems.

REFERENCES:

1. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. “Multivariate data analysis”, (7th edition). Pearson India. 2015
2. Tabachnick, B. G., & Fidell, L. S., “Using multivariate statistics”, (5th edition). Pearson Prentice Hall, 2001
3. Gujarati, D. N. , “Basic econometrics”, Tata McGraw-Hill Education, 2012
4. Malhotra, N. K., “ Marketing research: An applied orientation”, 5/e. Pearson Education India, 2008
5. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. “ Applied multiple regression/correlation analysis for the behavioral sciences”, Routledge., 2013
6. Han, J., Kamber, M., & Pei, J. “Data mining: concepts and techniques: concepts and techniques”, Elsevier, 2011.

Related posts:

  1. MA4159 Statistical Methods for Engineers Syllabus
  2. CN4101 Modern Construction Materials Syllabus
  3. CN4102 Project Formulation and Appraisal Syllabus
  4. CN4103 Construction Equipment and Management Syllabus
  5. RM4151 Research Methodology and IPR Syllabus
  6. ST4161 Advanced Construction Engineering and Experimental Techniques Laboratory Syllabus
  7. CN4111 Technical Seminar Syllabus
  8. CN4201 Advanced Construction Techniques Syllabus
  9. CN4202 Construction Planning, Scheduling, and Control Syllabus
  10. CN4203 Contract Laws and Regulations Syllabus
  11. CN4211 Construction Management Studio Laboratory Syllabus
  12. CN4212 Statistical Analysis for Construction Engineers Laboratory Syllabus
  13. CN4311 Practical Training (4 Weeks) Syllabus
  14. CN4312 Project Work I Syllabus
  15. CN4411 Project Work II Syllabus
  16. CN4071 Advanced Concrete Technology Syllabus
  17. CN4001 Human Resources Management in Construction Syllabus
  18. CN4002 Construction Project Management Syllabus
  19. CN4003 Sustainable Construction Syllabus
  20. CN4072 Economics and Finance Management in Construction Syllabus