Numerical and Statistical Methods for Computer Engineering
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Numerical and Statistical Methods for Computer Engineering Syllabus — Unit-wise Content
The official GTU curriculum for Numerical and Statistical Methods for Computer Engineering (subject code 2140706) as prescribed for Computer Engineering · Semester 4 divides the course into 7 units, covering 40 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 (2140706)Unit 1 Mathematical modeling andengineering problem
- Solving.Approximations and errors
- Significant figures
- accuracy and precision
- round-off and truncation errors
- error propagation
Unit 2 Roots of Equations
- Mathematical background
- NR method
- Successive approximation method
- Budan’s Theorem
- Barristow’s method
- case studies
Unit 3 Systems of linear algebraic equations
- Mathematical background
- Gauss elimination
- pitfalls and techniques for improvement
- matrix inversion and Gauss-Seidel methods
- ill- conditional Equations
- Predictor-Corrector methods
- case studies
Unit 4 Curve Fitting
- Mathematical background
- Least squares linear and polynomial regression
- Lagrange interpolating Polynomials
- Case studies
Unit 5 Numerical Integration
- Newton-Cotes integration formulas
- trapezoidalrule and Simpson’s rules: Interpolation
- case studies
Unit 6 Ordinary differential equations
- Euler’s method
- Runge-Kutta methods
- General methods for boundary value problems
- Case studies
Unit 7 Statistical Methods
- Frequency distributions
- Data analysis
- Expectations and moments
- Co- relation and regression
- Trend analysis
- Seasonal effects
- Cyclical Fluctuation
- Moving average, MSE, Predictions
- Non-parametric statistics
- Computer-based resampling techniques
- Confidence intervals and statistical significance
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