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Data Analytics IPU civil notes and question paper free download - Dipesh S - 04-25-2017

SYLLABUS:-

UNIT – I  
Preliminary Data Analysis: Graphical representation-line diagram or Bar Chart, Dot diagram, Histogram, Exploratory methods- stem and leaf plot, Box plot. Random events- sample space and  events, the null event, Intersection and  Union, Venn Diagram and  Event space. Continuous Distributions- Normal Distribution, Lognormal Distribution, Bivariate Normal Distribution.

UNIT – II  
Model Estimation and Testing: Properties of Estimators- Unbiasedness, Consistency, Minimum Variance, Efficiency, Sufficiency. Estimation of Confidence Intervals. Hypothesis testing- Procedure for testing, Probabilities of Type I and Type II Errors and the power function, Tests of Hypothesis involving the Variance, the F Distribution and  its use. Nonparametric methods- Wilcoxon Signed- Rank Test for Association of Paired Observations.

UNIT – III  
Goodness of Fit Tests: Chi-squared Goodness of Fit test, Kolmogorov- Smirnov Goodness of Fit test, Kolmogorov- Smirnov Two- sample test, Anderson- Darling Goodness of Fit test, Other methods for testing the Goodness of Fit to a Normal Distribution.  
Analysis of Variance: One-Way Analysis of Variance, Two-way analysis of Variance.  Probability Plotting for Normal Distribution, Probability Plotting for Type I Extreme Value Distribution. 
Identification and  Accomodation of Outliers: Hypothesis Tests, Test Statistics for Detection of Outliers, Dealing with Nonnormal Data.  
Estimation of Probabilities of Extreme events when outliers are present. Multivariate Analysis- Principle Components Analysis, Factor Analysis, Cluster analysis. 
Spatial Correlation: The Estimation problem, Spatial Correlation and  the Semivariogram, some Semivariogram Models and  Physical Aspects, Spatial Interpolations and  Kriging.

UNIT – IV  
Frequency Analysis of Extreme Events: Order Statistics- Functions of Order Statistics, Expected value and  Variance of Order Statistics, Expected Value and  Variance of Order Statistics. Extreme Value Distributions- Basic Concepts, Gumbel Distribution, Weibull Distribution as an Extreme Value Model, General Extreme Value Distribution. Analysis of Natural Hazards: Floods, storms and  Droughts, Earthquakes and  volcanic eruptions, winds, sea levels and  Highest sea waves.  
Simulation techniques for Design: MonteCarlo Simulation- Statistical Experiments, Probability Integral Tranform, Sample size and  accuracy of Monte Carlo Experiments.