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Statistics Assignment Help | Statistics Homework Help | Statistics Online Tutors

Globalwebtutors is known to have excellent team of Statistics Assignment experts with years of proven experience in Statistics Assignment help & Statistics homework help.

Our Statistics Online tutors are helping students with weekly Statistics homework assignments & the final year projects with excellent grades.

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Our Statistics Assignment help tutors offers excellent help with Statistical science, observational studies, statistical algorithms, game theory, high dimensional inference, information theory, nonparametric function estimation, model selection, time series analysis, probability theory.

  • Stochastic Processes ,Linear Modelling: Theory and Applications ,Sampling Surveys ,Time Series
  • Modern Statistical Prediction and Machine Learning ,Game Theory ,Design and Analysis of Experiments ,Reproducible and Collaborative Statistical Data Science
  • Descriptive statistics: diagrams and measures, Planning and design of statistical studies,Randomisation-based inference: interval and hypothesis test 

We at Globalwebtutors offer the best statistics assignment tutors in order to help the students struggling with Statistics assignments.

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Statistics assignment help is the need of university students pursuing degree programs in various discipline. Statistics Assignment is a nightmare for students if the thorough statistical concepts are missing. You need to have sound knowledge for statistical softwares & knowledge of analysis in order to solve the complex Statistics assignments.

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Some of the homework help topics include :  

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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

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    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. 

  • Binomial, Poisson, Gaussian distributions, decision trees, Maximum likelihood, asymptotic theory, nuisance parameters, score tests, Wald tests, Multivariate normal distribution, quadratic forms, general linear model
    Standard distributions, Statistical inference, Sampling distributions, Simple linear regression, Non-parametric tests, Wilcoxon signed-rank test

  • Bayesian inference with known priors, probability intervals ,Conjugate priors ,Frequentist significance tests and confidence intervals ,Resampling methods: bootstrapping ,Linear regression ,Computation, simulation, and visualization using R
  • 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 .

  • Time Series,Dynamic Regression ModelsPosterior Simulation and AR model ,Stochastic Volatility Models, Markov-Switching Models ,Latent Variable Models  ,Kalman Filter, FFBS ,Savage's theory ,coherence ,Arrow's impossibility theorem ,consensus, violations of Savage's postulate ,Imprecise Probability [IP] theory

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