Shulou(Shulou.com)06/01 Report--

How to carry out the descriptive statistics of R language in big data, many novices are not very clear about this. In order to help you solve this problem, the following editor will explain it in detail. People with this need can come and learn. I hope you can get something.

Common descriptive statistics can view the distribution and dispersion of data through minimum, lower quartile, median, upper quartile and maximum, mean, mode, standard deviation, range, etc.; check whether the data is normal or not through skewness (left or right deviation of data distribution) and kurtosis (distribution pattern of sharp thin or short fat).

The following is a brief description of how to use R to implement the above statistics of numeric variables.

1 the summary () function in the basic package

The minimum, lower quartile, median, upper quartile and maximum values of numeric variables can be obtained.

# using the self-contained mtcars dataset, select three numerical variables, mpg,disp and hp, for analysis. Head (mtcars) data

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.