R – Statistics

R Programming Language is used for environment statistical computing and graphics. The following is an introduction to basic R Statistics concepts like normal distribution (bell curve), central tendency (the mean, median, and mode), variability (25%, 50%, 75% quartiles), variance, standard deviation, modality, and skewness.

R – Statistics

Statistics is a form of mathematical analysis that concerns the collection, organization, analysis, interpretation, and presentation of data. Statistical analysis helps to make the best use of the vast data available and improves the efficiency of solutions.

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R – Statistics

R Programming Language is used for environment statistical computing and graphics. The following is an introduction to basic R Statistics concepts like normal distribution (bell curve), central tendency (the mean, median, and mode), variability (25%, 50%, 75% quartiles), variance, standard deviation, modality, and skewness....

Data Concepts

Data can be formed in different structures and different formats, before starting the concepts of R Statistics we need to know the data formats....

Statistics in R

Average, Variance and Standard Deviation in R Mean, Median and Mode in R Programming Probability in R Discrete distributions Benford Distribution Bernoulli Binomial Hypergeometric distribution Geometric distribution Multinomial Negative binomial distribution Poisson distribution Zipf’s law Continuous distributions Beta distributions Dirichlet distributions Cauchy Chi-Square distribution Exponential Fisher-Snedecor Gamma Levy Log-normal distribution Normal and related distributions Pareto Distributions Student’s t distribution Uniform distribution Weibull Calculate Conditional Probability Binomial Distribution  Normal Distribution in R Beta Distribution in R Hypothesis in R Types of Hypothesis Null Hypothesis Alternative Hypothesis  One Sample T-Testing Two Sample T-Testing Paired Sample T-test Decision Errors in R  Type I Error Type II Error Confidence Intervals Correlation and Covariance Covariance Matrix Pearson Correlation Normal Probability Plot Quantile Quantile plots Residuals Leverage Plot Spearman’s Rank Correlation Measure Kendall Rank Correlation Measure Evaluation Metrics – Accuracy, Precision, Recall, F1-Score, MAE, MSE Root-Mean-Square Error ROC and AUC curve...

Plotting graphs in Statistics in R Programming Language

Following is a list of functions that are required to plot graphs for the representation of R Statistics data:...

Bar charts

A Bar chart represents categorical data with rectangular bars where the bars can be plotted vertically or horizontally....

Pie charts

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Histograms

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Box Plots

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