What is R Programming?
R is a very flexible and powerful programming language, as well as a package that is written using that language (and others like C).
R- Programming is a language and environment developed by Bell Laboratories (popularly known as AT&T) for statistical computing and graphics.
List of topics which we have covered in this blog are:
Random variables: definition, programming examples in R
Bayesian statistics
Mayor continuous and discrete probability distribution functions (PDF): normal (Gaussian), uniform, exponential, Pascal, binomial, etc; cumulative distribution (density) function (CDF)
Linear univariate and multivariate regression and modeling
Frequentist and Bayesian inference: p-values and confidence intervals
Model selection; information criterionsNon-parametric statistics
Statistical tests, such as ANOVA, Student's t-test, F-test, Chi-square test
Analysis of variance
Exploratory Data Analysis (EDA)
High-dimensional data analysis (Singular value decomposition (SVD), Principal component analysis (PCA))
Data visualization techniques
Basic Machine Learning concepts
Other Sub-Topics for R Programming Assignment
Robust regression
Logistic regression
Exact logistic regression
Multinomial logistic regression
Ordinal logistic regression
Probit regression
Poisson regression
Negative binomial regression
Zero-inflated Poisson regression
Zero-inflated negative binomial regression
Zero-truncated Poisson
Zero-truncated negative binomial
Censored and truncated regression
To bit regression
Truncated regression
R Libraries in which is our team have an expertise
tidyverse (general R library including some of the libraries below)
ggplot2
dplyr
tidyr
readr
purrr
tibble
stringr
plotly (interactive graphs)
stargazer (beautiful regression tables)
R Markdown
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