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R and Excel for statistical analysis ,statistical methodology ,Measuring and Describing Variables ,Probability and Distributions of Random Variables ,Confidence Intervals and Hypothesis Testing
Null and Alternative Hypotheses, Permutations and Combinations, Poisson Distributions, P-Values Regression Analysis, Sample Bias and Distribution, SPSS, Statistical Graphs, Stochastic Processes and Modeling, Student T-Distribution, T-Tests, Uniform Distributions, Z-Scores, Applied probability, Resampling methods.
Descriptive statistical techniques, regression, design of sample surveys and experiments, basic probability, statistical inference ,
Interpretation of results of statistical procedures in addition to problem solving ,data analysis,Minitab ,statistical computing
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Time Series, Model Selection and Logistic Regression, Market Model, Bayesian Inference, Dynamic Linear Models, Dynamic Regression Models, Posterior Simulation and AR model Stochastic Volatility Models, Markov-Switching Models, Latent Variable Models, FFBS.
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Standard distributions, Statistical inference, Sampling distributions, Simple linear regression, Non-parametric tests, Wilcoxon signed-rank test
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Categorical data analysis, log-linear models, nonparametric methods ,MegaStat , Multilevel Longitudinal Modelling ,Nonlinear Dynamics Analysis, SPSS Amos- SEM ,Reliability Theory ,SPSS- Factor Analysis, Black Scholes Theory , Excel Minitab, Survey Methodology .
Risk Modelling, Derivatives Modelling , Mathematical Programming Algorithms, EViews ,LISREL boxplot,Non-Gaussian Models .
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