# 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 perform analysis using descriptive statistics, and one of them is by using the base R functions and packages such as “stats” or “psych” package.

To perform analysis using descriptive statistics in R, you first need to load the data into R. Once the data is loaded, you can use the summary() function to get a summary of the basic statistics of the data, such as the mean, median, and standard deviation. You can also use other functions such as min(), max(), quantile() to get the minimum, maximum, and quantiles of the data. Additionally, you can use the table() function to get the frequency of observations.

It’s worth noting that Descriptive statistics are used to give a quick overview of the data and to find patterns or trends in the data. Descriptive statistics are also useful for identifying outliers and skewness in the data. R has a vast number of packages and functions that are available for descriptive statistics, and it’s a good idea to consult with experts before performing analysis using descriptive statistics, to make sure you are using the best suited method for your data.

In summary, 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 perform analysis using descriptive statistics, and one of them is by using the base R functions and packages such as “stats” or “psych” package. To perform analysis using descriptive statistics in R, you first need to load the data into R. Once the data is loaded, you can use the summary() function to get a summary of the basic statistics of the data, such as the mean, median, and standard deviation. You can also use other functions such as min(), max(), quantile() to get the minimum, maximum, and quantiles of the data. Additionally, you can use the table() function to get the frequency of observations. It’s worth noting that Descriptive statistics are used to give a quick overview of the data and to find patterns or trends in the data. Descriptive statistics are also useful for identifying outliers and skewness in the data. R has a vast number of packages and functions that are available for descriptive statistics, and it’s a good idea to consult with experts before performing analysis using descriptive statistics, to make sure you are using the best suited method for your data.

In this Applied Machine Learning Recipe, you will learn: How to perform analysis using Descriptive Statistics in R.