IL4211 Data Analytics Laboratory Syllabus:

IL4211 Data Analytics Laboratory Syllabus – Anna University PG Syllabus Regulation 2021

OBJECTIVES:

 Training and Exposure on Correction Analysis, Simple and Multiple Regression.
 Training and Exposure on Factor Analysis, Discriminant and Cluster Analysis.
 Training and Exposure on Control Charts for Variable and Attributes.
 Training and Exposure on Predicting Reliability Parameters.
 Training and Exposure on Analysis of Variance.

LABORATORY EXPERIMENTS

1. Determine the linear regression model for fitting a straight line and calculate the least squares estimates, the residuals and the residual sum of squares.
2. Determine the multivariate regression model for fitting the straight line.
3. Perform the Correlation analysis to determine the relationships among the variables.
4. Perform the factor analysis for the given set of model data using both Exploratory and Confirmatory methods and evaluate the model adequacy.
5. Determine which continuous variable discriminate among the given group and determine which variable is the best predictor.
6. Determine the groups using Cluster Analysis
7. Determine the process is within the control or not by developing the control charts for attributesand variables and estimate the process capability.
8. Estimate the parameters (MTTF, MTBF, failure rate, bathtub curve etc) of components and systems to predict its reliability.
9. Develop the single factor and two factor design of experiment model to predict the significance factor.
10. Develop 2K factorial and 2k-p fractional factorial experiment to determine the parameters which affect the system.

TOTAL : 60 PERIODS

OUTCOMES:

CO1: Ability to independently formulate, perform and assess hypothesis
CO2: Ability to select appropriate technique
CO3: Ability to apply selected data analysis techniques
CO4: Ability to interpret the results
CO5: Ability to present the results properly to extract meaningful information from data sets for effective decision making.