Statistical Techniques for Data Analysis
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Follow on Instagram for UpdatesStatistical Techniques for Data Analysis Syllabus — Unit-wise Content
The official GTU curriculum for Statistical Techniques for Data Analysis (subject code ME01069041) as prescribed for C(E · Semester 1 divides the course into 9 units, covering 75 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 (ME01069041)Unit 1 Introduction
- Statistics and Engineering
- Basic concept – Population and Sample
- Frequency distribution
- Stem and Leaf displays
- Descriptive measures
- Quartiles and Percentiles
Unit 2 Probability
- Sample space and Events
- Axioms of probability
- Elementary theorems of Probability
- Conditional probability
- Bayes’ Theorem Program Name: Master of Engineering Level: PG Branch: Civil Engineering (Transportation Engineering) Course / Subject Code: ME01069041 Course / Subject Name: Statistical Techniques for Data Analysis
Unit 3 Probability Distributions
- Random variables
- Binomial distribution
- Hypergeometric distribution
- Mean and variance of a probability distribution
- Poisson distribution
- Geometric and Negative Binomial distribution
- Multinomial distribution
Unit 4 Probability Densities
- Continuous random variables
- Normal distribution
- Other probability densities
- Uniform distribution
- Log- Normal distribution
- Moment generating function
- Sampling distribution of mean
Unit 5 Statistical Inference and Tests of Significance
- Hypothesis testing
- types of error in hypothesis
- confidence interval
- significance tests for comparing variances and means
- tests with small and large samples
- two-tail and one-tail student’s t-test
- analysis of variance (ANOVA)
- non-parametric tests (Chi-square test and Kolmogorov–Smirnov test)
- central limit theorem
- practice with transportation data
Unit 6 Sampling Techniques
- Sample surveys
- sampling bias
- random sampling
- stratified sampling
- sequential sampling
- cluster sampling
- systematic sampling
- sampling on successive occasions
- non-sampling errors
- applications in transportation engineering
Unit 7 Regression and Correlation
- Simple linear regression
- residuals and variances
- multiple linear regression
- two-stage regression
- backward and step-wise regression
- residual analysis
- correlation analysis
- type of correlations
- coefficient of correlation
- Karl-Pearson’s coefficient
- multivariate data analysis
- factor analysis
- applications in transportation engineering
Unit 8 Parameter Estimation and Curve Fitting Techniques
- Least square
- generalized least squares
- method of moments
- maximum likelihood
- algebraic and geometric curve fit, linear and non-linear curve fitting (polynomial
- overfit, and under fit
Unit 9 Time Series Models
- Time series concept and components
- time series models
- measurement of time series
- graphical method
- method of semi-average
- moving average
- least square
- parabolic and logarithmic trends
- growth curves
- ratio-to-trend and link relative method for seasonal variation
- exercises with transportation data
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