Mean vector and variance-covariance matrix

Multivariate kansverdelingen in R

Surajit Ray

Professor, University of Glasgow

Mean represents the location of the distribution

Mean $0.95$

Mean vector (0.95 1.89)

Variance-covariance matrix is the spread

Variance $1.02$

Variance-covariance ${\begin{pmatrix} 1.02 & 0.97 \\ 0.97 & 2 \end{pmatrix}}$

Calculating the mean

colMeans(iris_raw[, 1:4])

Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
        5.84         3.05         3.76         1.20

Functions that calculate means by subgroups

by()
aggregate()

Calculating the group mean using by

by(data = iris[,1:4], INDICES = iris$Species, FUN = colMeans)

iris_raw$Species: setosa
Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
       5.006        3.418        1.464        0.244 
 ----------------------------------------------------
iris_raw$Species: versicolor
Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
       5.936        2.770        4.260        1.326 
 ----------------------------------------------------
iris_raw$Species: virginica
Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
       6.588        2.974        5.552        2.026

Calculating the group mean using aggregate

aggregate(. ~ Species, iris_raw, mean)

     Species Sepal.Length Sepal.Width Petal.Length Petal.Width
1     setosa         5.01        3.42         1.46       0.244
2 versicolor         5.94        2.77         4.26       1.326
3  virginica         6.59        2.97         5.55       2.026

Calculating the variance-covariance and correlation matrices

var(iris_raw[, 1:4])

             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length       0.6857     -0.0393        1.274       0.517
Sepal.Width       -0.0393      0.1880       -0.322      -0.118
Petal.Length       1.2737     -0.3217        3.113       1.296
Petal.Width        0.5169     -0.1180        1.296       0.582

Correlation

cor(iris_raw[, 1:4])

             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length        1.000      -0.109        0.872       0.818
Sepal.Width        -0.109       1.000       -0.421      -0.357
Petal.Length        0.872      -0.421        1.000       0.963
Petal.Width         0.818      -0.357        0.963       1.000

Visualization of correlation matrix

corrplot function to visualize correlation plot

corrplot(cor(iris_raw[, 1:4]), method = "ellipse")

Interpretation of means

Means

Species	Petal.Length	Petal.Width
setosa	1.46	0.244
versicolor	4.26	1.326
virginica	5.55	2.026

mean

Interpretation of variances

setosa	Petal.Length	Petal.Width
Petal.Length	0.030	0.006
Petal.Width	0.006	0.011

versicolor	Petal.Length	Petal.Width
Petal.Length	0.221	0.073
Petal.Width	0.073	0.039

virginica	Petal.Length	Petal.Width
Petal.Length	0.305	0.049
Petal.Width	0.049	0.075

mean and variance

Let's practice!

Multivariate kansverdelingen in R