IM3711 - Data Analytics Laboratory Syllabus Regulation 2021 Anna University

Subject code IM3711 deals with semester VII of the Data Analytics Laboratory Syllabus of Anna University based on regulation 2021. In this article, we would like to discuss the syllabus of Data Analytics Laboratory. Let’s see.

We aim to provide the unit-wise IM3711 – Data Analytics Laboratory syllabus. It will avoid confusion for students during the examination period. We added the required textbooks and references to the syllabus. I hope this information is useful. You better be quick to read the syllabus prior than the others and prepare well for examinations. Kindly read this article thoroughly and then share it with your classmates. A decent qualified certificate from the university will help you to reach heights The following syllabus will assist you.

If you want to know more about the syllabus of B.E. Industrial Engineering and Management connected to an affiliated institution’s four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E. Industrial Engineering and Management Syllabus Regulation 2021 Anna University.

Aim Of Objectives:

This course aims to:

  • Design a data analysis strategy that answers a hypothesis, including specifications for data elements, requirements of the statistic, and limitations to the interpretation.
  • Understand how to select appropriate techniques.
  • Understand how to conduct a variety of statistical analyses, including testing of statistical assumptions, data transformations, and validation of statistical findings.
  • Understand how to interpret the results of statistical analyses.
  • Understand how to present the results of statistical analyses.

Students will perform analysis of data in the following topics using Data Analysis package

  1. Control Charts
  2. Correlation Analysis
  3. Simple Regression
  4. Multiple Regression
  5. Single factor Experiment
  6. Factorial experiment
  7. Factor Analysis
  8. Discriminant Analysis
  9. Cluster Analysis
  10. Estimation of model parameters of the system to predict Reliability.

Related Posts On Semester – VII:

Must Read: