Regression Analysis in R – How to visualise Visualization is the process of creating graphical representations of data to make it easier to understand and analyze. In R, there are several ways to visualize data, and one of them is by using the base R functions and packages such as “ggplot2”, “lattice” and “plotly”. The …

Regression Analysis in R – How to use predict function Regression analysis is a statistical method that is used to examine the relationship between one or more independent variables and a dependent variable. In R, there are several ways to perform regression analysis, and one of them is by using the base R functions and …

How to perform analysis using Descriptive Statistics in R Descriptive statistics is a branch of statistics that deals with summarizing and describing data. Descriptive statistics are used to describe and understand the characteristics of a data set, such as the mean, median, standard deviation, and frequency of observations. In R, there are several ways to …

How to generate Violin plots in R using ggpubr package A Violin plot is a combination of a boxplot and a kernel density plot, which shows the distribution of a set of continuous data. It can be useful to visualize the spread and skewness of the data and to identify outliers. In R, there are …

How to generate Boxplots in R using ggpubr package A Boxplot, also known as a Whisker plot, is a standardized way of displaying the distribution of data based on five number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It can be useful to visualize the spread and skewness of the data …

How to generate histograms in R using ggpubr package A histogram is a graph that shows the distribution of a set of continuous data by dividing the data into a series of bins and counting the number of data points that fall into each bin. In R, there are several ways to generate histograms, and …

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How to utilize ggplot to visualise Data – scatter plots in R Visualizing data is an important step in understanding and interpreting the results of an analysis. One way to visualize data in R is by using the ggplot2 library, which is a powerful data visualization tool. One of the most common types of plots …

How to compare performance of different trained models in R Comparing the performance of different trained models is an important step in the model selection process. It allows you to evaluate how well each model is able to make predictions and to choose the best model for your problem. In R, there are several ways …

How to save trained model in R After training a model in R, it is often useful to save the model so that it can be used later without having to retrain it. R provides several ways to save a trained model, which include the save(), saveRDS(), and save() functions in the caret package. These …