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R Programming Assignment Help , R Homework help


 We at Global web tutors provide expert help for R programming assignment or R programming homework. Our R programming online tutors are expert in providing homework help to students at all levels.

Please post your assignment at support@globalwebtutors.com to get the instant R programming homework help. R programming online tutors are available 24/7 to provide assignment help as well as R programming homework help.

R Programming

R programming deals with statistical computation to define the user graphic interface which provides the open-source and free environment development for the implementation of the problems.

The important topics include data mining and warehousing,Hypothesis test,Clustering,Time series analysis,Regression modeling

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R Programming Assignment help :

  • RStudio,R Markdown,data types,operations,numbers,characters ,composites,Vectors,creating sequences,common functions,tabular data,continuous data,R style,data frames,Multivariate statistical summaries ,ggplot2 graphics,QQ plots,ANOVA,Linear regression,multicollinearity,Diagnosing,interpreting regression,plyr package,split-apply-combine
  • language elements ,R+Knitr+Markdown+GitHub,Data input,output,Data storage formats,Subsetting objects,Vectorization,Control structures,Functions,Scoping Rules,Loop functions,data manipulation ,dplyr ,profiling,Statistical simulation ,S3,S4,Reference classes,Performance profiling.
  • Predicting Algae Blooms,Descriptive statistics,,Data visualization,,Strategies to handle unknown variable values,,Regression tasks,,Evaluation metrics for regression tasks,,Predicting Algae Blooms,Multiple linear regression,,Regression trees,,Model selection/comparison through k-fold cross-validation,,Detecting Fraudulent Transactions,Clustering methods,,Classification methods,,Imbalanced class distributions and methods ,Naive Bayes classifiers,Precision/recall and precision/recall curves,Classifying Microarray Samples,Feature selection methods for problems with a very large number of predictors,Random forests,k-Nearest neighbors
  • R programming techniques, statistical analyses,data objects,loops,importing/exporting datasets,graphics,t-tests,ANOVA,linear regression,non parametric tests,logistic regression
  • Overview of R, R data types and objects, reading and writing data ,Control structures, functions, scoping rules, dates and times ,Loop functions, debugging tools ,Simulation, code profiling ,swirl Programming

  • R statistical package for data analysis,R for descriptive statistics , graphics, inferential statistical analyses ,regression analysis, read and write data files, data manipulations ,R script files, R functions

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