R language Note 005--computational descriptive statistics

Distribution characteristics of the data:

• The concentration trend of the distribution, the degree to which each data is aligned or aggregated to its central value (average, median, four, number of digits)
• The degree of dispersion of the distribution, the tendency to reflect the data away from its central value (very poor, four-bit difference, variance, standard deviation, discrete coefficients)
• The shape of the distribution, the degree of skewness and kurtosis of the distribution of the reaction data (skewness coefficient, kurtosis coefficient)

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average (mean): A group of data is added and divided by the number of data to get the result, called the average (mean)

Median: The value of the variable in the middle position after a set of data is sorted , called the median (median)

Four : The value of a set of data in 25% (lower four-digit) and 75% (top four-digit) positions after sorting, called four-cent

• The position is calculated first, and then the value of the four-bit number is calculated. 50% is the median

Majority : The number of the most frequently occurring numbers in a set of data (mode)

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Extreme (Full): The difference between the maximum and minimum values of a set of data, called the Extreme Difference (range)

Four differential: The difference between the four and the lower four, called the four-cent difference

mean difference : The average difference between the values of each variable and its average deviation, called the mean

Variance : The average of the squared deviations of each variable value from its average, called variance (variance)

Standard deviation : The square root of the variance is called the standard deviation ()

Discrete coefficients :

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skewness : Asymmetry of data distribution, called Skewness

Peak State : The level of the peak or peak of the data distribution, called the peak state

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Descriptive statistics: mainly includes the degree of concentration of distribution, the degree of dispersion of distribution and the extent of skewness of distribution.

Method One: summary () function--Max, Min, four min (top, bottom), mean

Summary (Mtcars) #结果有以下几条

1 vars<-c ('mpg','hp','wt ' )2 Head (Mtcars[vars])

Summary (Mtcars[vars])

R language Note 005--computational descriptive statistics