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R Programming Assignment Help

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R Programming Assignment Help

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What is R Programming?

R-Programming is a language and condition created for statistical computing and graphics developed by Bell Laboratories prominently known as AT&T. The measurable direct and non-liner model is likewise included for its gathering of statistical assignments. Benefiting R programming homework help in Australia from the specialists is valuable to find out about R-language and programming alongside its uses.

R is a GNU venture that is like the S language and condition which was created at Bell Laboratories, presently known as Lucent Technologies, by John Chambers during the 80s. R can be estimated as an alternate execution of S. There are some huge contrasts between the two, yet the greater part of the code is composed for S language likewise run under R consummately.

List of R Programming Assignment Help Topics

Simple Linear Regression

Multiple regression

Logistic Regression

Multivariate analysis

Time series

Econometrics

Non-parametric tests

ANOVA

Probability Theory

Null Hypothesis

Statistical Inference

Box plot

Chi-square test

Stochastic process

Sampling

Monte Carlo simulation

Bootstrapping

Scatter plot

Biostatistics

Correlation analysis

Statistical process control

Parametric tests

Markov chains analysis

Central Limit Theorem

Career Aspects of R Programming by Experts

Some of the achievable career aspects are for R programming assignment help experts are below:

  • Biosimilars Program Manager
  • System Programming Specialist
  • Programming Manager
  • Object-Oriented Programmer
  • Data Analyst and Programmer

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Sample of R Programming Homework Help Solved

  1. Using the provided dataset on grades, repeat the steps on the slide deck about R (the Rprimer). You can also use your own dataset or the one on wages (but would have to adjust the variable names, obviously).
  2. The slides show several distributions: binomial, Poisson, normal, Chi-Squared, F, and the t distribution. Choose at least 3 distributions o Preferably in R, simulate data (e.g. 5000 draws) from a Random Variable that follows this distribution.
  • What is the Expectation and the Variance of your simulated variable?
  • Draw a histogram based on your simulated data.
  • Try to plot the distribution using qplot
  • As in the problem set, think:
  • What is the code or its output is the analogon of the random variable? Comment how you reach your conclusion.
  • What is the code or its output is the analogon of an outcome? Comment how you reach your conclusion.
  • What is the code or its output contains the analogon of a population/sample? Comment how you reach your conclusion.
  • Calculate the sample mean and the sample variance.
  • Compare them to the theoretical mean and variance that you programmed. Are they exactly the same? Why/Why not?
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