Course Details
Subject {L-T-P / C} : CH4374 : Chemical Engineering Data Analysis Laboratory { 0-0-2 / 1}
Subject Nature : Practical
Coordinator : Abanti Sahoo
Syllabus
| Module 1 : |
Various types of data, data presentation including bar chart pie-chart Histogram stem chart etc. Data pre-processing including outlier detection techniques, filtering and smoothening. Determination of data statistics including mean mode variance co-variance confidence interval various distributions (Gaussian and others) statistical inference estimation, correlation and regression analysis Hypothesis testing chi-square distribution precision and accuracy, hence the acceptance of data generated. All the activities are to be done using MATLAB and SPSS ( Statistical Package for the Social Sciences) software packages. |
Course Objective
| 1 . |
To make the students learn the attributes of data and its effective presentation. |
| 2 . |
Data preprocessing including data outlier detection, data filtering, and data smothering. |
| 3 . |
Non-stationary behavior of data and its conversion to stationary data. |
| 4 . |
Statistical interpretation of data. |
Course Outcome
| 1 . |
1. Enable the students to analyze and present data effectively.
|
Essential Reading
| 1 . |
Robert M. Bethea, Statistical Methods for Engineers and Scientists, CRC Press , 3rd Edition, 2019 |
| 2 . |
M.Kundu, P. Kundu, S. K. Damarla, A Chemometric Approach to Monitoring: Product Quality Assessment, Process Fault Detection and Miscellaneous Applications, CRC Press, Taylor & Francis Group , 2017 |
Supplementary Reading
| 1 . |
SPSS tutorial, SPSS tutorial, IBM , 2017 |
Journal and Conferences
| 2 . |
Chemometrics and Intelligent Laboratory Systems, Elsevier Publication |
| 1 . |
Journal of Chemometrics, Elsevier Publication |