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BBL772: Difference between revisions

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| credit_structure = 2-0-2
| credit_structure = 2-0-2
| pre_requisites = Basic Mathematics (Class 10 level)
| pre_requisites = Basic Mathematics (Class 10 level)
| overlaps = SBL701, MSL874
| overlaps = [[SBL701]], [[MSL874]]
}}
}}


== BBL772 : Data Analytics and Informatics for Biotechnology ==
== BBL772 : Data Analytics and Informatics for Biotechnology ==
Module 1 (Statistics for engineers) • Introduction to data in Biotechnological applications and Error Analysis • Introduction to statistical programming • Data visualization; Measures of Location and Dispersion • Probability and Common Probability Distributions • Point Estimation and central limit theorem • Confidence Interval, Hypothesis Testing and Types of errors • Regression for engineers, Correlation, and Calibration • Design and Analysis of Experiments Module 2 (Bioinformatics) • Bioinformatic data generation technologies • Bioinformatic databases • Essential problems in Bioinformatics - Alignment, Assembly, Mapping
Module 1 (Statistics for engineers) • Introduction to data in Biotechnological applications and Error Analysis • Introduction to statistical programming • Data visualization; Measures of Location and Dispersion • Probability and Common Probability Distributions • Point Estimation and central limit theorem • Confidence Interval, Hypothesis Testing and Types of errors • Regression for engineers, Correlation, and Calibration • Design and Analysis of Experiments Module 2 (Bioinformatics) • Bioinformatic data generation technologies • Bioinformatic databases • Essential problems in Bioinformatics - Alignment, Assembly, Mapping

Latest revision as of 16:23, 14 April 2026

BBL772
Data Analytics and Informatics for Biotechnology
Credits 3
Structure 2-0-2
Pre-requisites Basic Mathematics (Class 10 level)
Overlaps SBL701, MSL874

BBL772 : Data Analytics and Informatics for Biotechnology

Module 1 (Statistics for engineers) • Introduction to data in Biotechnological applications and Error Analysis • Introduction to statistical programming • Data visualization; Measures of Location and Dispersion • Probability and Common Probability Distributions • Point Estimation and central limit theorem • Confidence Interval, Hypothesis Testing and Types of errors • Regression for engineers, Correlation, and Calibration • Design and Analysis of Experiments Module 2 (Bioinformatics) • Bioinformatic data generation technologies • Bioinformatic databases • Essential problems in Bioinformatics - Alignment, Assembly, Mapping