Statistical Techniques for Environmental Engineering

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STATISTICAL TECHNIQUES FOR BE03013041
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Code: BE03013041 Credits: 4 Semester 3 Env. Engg

Statistical Techniques for Environmental Engineering

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

Statistical Techniques for Environmental Engineering Syllabus — Unit-wise Content

The official GTU curriculum for Statistical Techniques for Environmental Engineering (subject code BE03013041) as prescribed for Env. Engg · Semester 3 divides the course into 4 units, covering 29 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 (BE03013041)

Unit 1 Statistical Techniques for Environmental Engineering, Types of statistical

10 lecture hours

  • Applications of statistical data in Environmental Engineering field
  • common statistical terms
  • sources for statistical data collection
  • Methods of presentation of data: tabularization and drawing
  • Presentation of quantitative data: histogram
  • frequency distribution
  • frequency polygon
  • frequency curve
  • line chart
  • scatter diagram
  • Presentation of qualitative data: Bar diagram
  • Pie diagram
  • Map Diagram

Unit 2 Measures of Central tendency

12 lecture hours

  • Averages- Mean
  • Mode Partition Values: Quartiles
  • Measurement of Variability: Real and Experimental Measures of Variability of Individual Observations: Range
  • Mean deviation
  • Standard Deviation
  • Coefficient of Variation Measures of Dispersion: Range
  • Quartile deviation
  • relative measures of dispersion

Unit 3 Skewness and its measures, kurtosis and its measures, Correlation and

11 lecture hours

  • regression : Biviriate data
  • correlation analysis
  • Coefficient of determination
  • Regression Analysis

Unit 4 Probability

12 lecture hours

  • Basic concepts
  • laws of probability
  • testing of hypothesis: large sample test and small sample test
  • analysis of variance: one way analysis of variance and two analysis of variance

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