Category: R

R Summary Statistics Table

R Summary Statistics Table, The describe() and describeBy() methods from the psych package are the simplest way to produce summary tables in R. library(psych) The syntax for the summary table tidyverse in r –...

Group wise Correlation in R

Group-wise Correlation in R, To calculate the correlation between two variables by the group in R, use the basic syntax below. library(dplyr) df %>%   group_by(group) %>%   summarize(cor=cor(var1, var2)) This syntax computes the...

String pad to the column in R

String pad to the column in R, padding the string to the left, right, or on either side of the column can be done in three ways. We’ll look at how to do it...

Bootstrap Confidence Interval R

Bootstrap Confidence Interval R, Bootstrapping is a technique for estimating the standard error of any statistic and generating a confidence interval for it. The following is the fundamental bootstrapping procedure, From a given dataset,...

How to remove Scientific Notation in R

How to remove Scientific Notation in R, To disable scientific notation in R, use the following methods: The examples below demonstrate how to utilize each of these strategies in practice. Method 1: As a...

How to Add Text to a Plot in R

In base R, the text() function can be used to add text to a plot. The following is the fundamental syntax for this function text(x, y, “my text”) where: x, y: The text should...

How to calculate proportion in a table

Calculate proportion in a table, To determine the value of each cell in a table as a proportion of all values, use the prop.table() function in R. The following is the fundamental syntax for...

How to Calculate a Bootstrap Standard Error in R

Bootstrap Standard Error in R, Bootstrapping is a technique for calculating the standard error of a mean. The following is the basic procedure for calculating a bootstrapped standard error. Model Selection in Machine Learning...

Confidence Intervals Explained

A confidence interval (CI) is a set of numbers that most likely contains the value of an unknown population parameter. Given the properties of your sample data, these intervals represent a realistic domain for...

Predictive Analytics Models in R

Predictive analytics models are crucial in the fields of data science and business analytics, and they have a big impact on a lot of different business operations. Depending on the data amount in terms...