Statistics for Engineers

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STATISTICS FOR ENGINEERS 2714601
FREE PDF 2714601
Code: 2714601 Credits: 5 Semester 1 M(E

Statistics for Engineers

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Statistics for Engineers Syllabus โ€” Unit-wise Content

The official GTU curriculum for Statistics for Engineers (subject code 2714601) as prescribed for M(E ยท Semester 1 divides the course into 6 units, covering 24 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (2714601)

Unit 1 Discrete Distributions

6 lecture hours

  • Random variables
  • Standard probability distributions-Binomial
  • Poisson and Geometric distributions
  • Moment generating function of respective distributions
  • Two dimensional random variables

Unit 2 Continuous Distributions

5 lecture hours

  • Special distributions- Normal
  • Weibull and Beta distributions - Mean
  • Raw moments from moment generating functions of respective distributions

Unit 3 Sampling Distributions

6 lecture hours

  • Random Sampling
  • Sampling distributions of mean and variance
  • F-test and Chi-square test

Unit 4 Estimation Theory

5 lecture hours

  • Estimation of Parameters
  • Maximum likelihood estimates
  • Confidence interval estimation of population parameters Method of moments

Unit 5 Hypothesis Testing

5 lecture hours

  • Large sample tests for mean and proportion
  • Non parametric tests
  • Goodness of fit tests
  • Analysis of variance - One way and two way classifications

Unit 6 Design of Experiments

7 lecture hours

  • Completely Randomized Design
  • Randomized Block design
  • Latin square design - 2 Factorial Design
  • Fundamental Assumptions of analysis of variance
  • Single factor experiments โ€“ Fixed/random effects model โ€“ Model adequacy checking - Multiple comparisons - Design of experiments with several factors - Two factor factorial experiments
  • Taguchi Approach to Design of Experiments - The

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