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The R programming language, commonly called just "R," is developed as a free language that is utilized for graphics aid and statistical computing. One can utilize various statistical methods and graphical techniques to solve statistics and graphic computations. Besides this, this language is connected with different languages like clustering, statistical hypothesis, data mining, regression modeling, data warehousing, etc. If your teacher asked you to write an R programming assignment in a short time, then you can avail of our R programming assignment help or Rstudio assignment help service. We have years of experienced prommers who have immense programming knowledge and will guarantee you to provide the best quality assignment.
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R is an open-source language that is commonly recognized as R is developed for statistical computing. It forms a statistical environment to perform statistical graphics and computing. This programming language is utilized by the statisticians and data miners to interpret data and generate statistical software. Managing polls, examining the databases of literature, and doing surveys have raised the R language demand in the past few years.
# String
y <- "R is Fantastic"
class(y)
## [1] "character"
# Declare variables of different types
# Numeric
x <- 28
class(x)
## [1] "numeric"
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Several students do not concentrate on the lessons which are taught in the class because of any reason. By which they miss important things that were discussed in the class. These are things that are useful in writing your R programming assignment. Most of the assignments are based on the things which are taught in the class.
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Logistic Regression | Multivariate analysis |
Non-parametric tests | ANOVA |
Alternate Hypothesis | Chi-square test |
Sampling | Box plot |
Central Limit Theorem | Monte Carlo simulation |
Markov chains analysis | Statistical process control |
Stochastic process | Time series |
Simple Linear Regression | Multiple regression |
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Design of Experiments | Null Hypothesis |
Probability Theory | Hypothesis Tests and confidence intervals |
Bootstrapping | Scatter plot |
Statistical Inference | Biostatistics |
Distribution Theory | Econometrics |
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