pearson相关分析在R中的实现

三个相关性函数：

cor():R自带的，输入数据可以是vector，matrix，data.frame，输出两两的相关系数R值

cor.test()：R自带的，输入数据只能是两个vector，输出两个变量的相关系数R值，显著性水平a值

corr.test()：psych包的，输入数据可以是data.frame，输出两两变量的相关系数R值，显著性水平a值

> cor(state.x77)
            Population     Income  Illiteracy    Life Exp     Murder     HS Grad      Frost        Area
Population  1.00000000  0.2082276  0.10762237 -0.06805195  0.3436428 -0.09848975 -0.3321525  0.02254384
Income      0.20822756  1.0000000 -0.43707519  0.34025534 -0.2300776  0.61993232  0.2262822  0.36331544
Illiteracy  0.10762237 -0.4370752  1.00000000 -0.58847793  0.7029752 -0.65718861 -0.6719470  0.07726113
Life Exp   -0.06805195  0.3402553 -0.58847793  1.00000000 -0.7808458  0.58221620  0.2620680 -0.10733194
Murder      0.34364275 -0.2300776  0.70297520 -0.78084575  1.0000000 -0.48797102 -0.5388834  0.22839021
HS Grad    -0.09848975  0.6199323 -0.65718861  0.58221620 -0.4879710  1.00000000  0.3667797  0.33354187
Frost      -0.33215245  0.2262822 -0.67194697  0.26206801 -0.5388834  0.36677970  1.0000000  0.05922910
Area        0.02254384  0.3633154  0.07726113 -0.10733194  0.2283902  0.33354187  0.0592291  1.00000000
> cor.test(state.x77[,1],state.x77[,2])

	Pearson's product-moment correlation

data:  state.x77[, 1] and state.x77[, 2]
t = 1.475, df = 48, p-value = 0.1467
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.07443435  0.45991855
sample estimates:
      cor
0.2082276 

> corr.test(state.x77)
Call:corr.test(x = state.x77)
Correlation matrix
           Population Income Illiteracy Life Exp Murder HS Grad Frost  Area
Population       1.00   0.21       0.11    -0.07   0.34   -0.10 -0.33  0.02
Income           0.21   1.00      -0.44     0.34  -0.23    0.62  0.23  0.36
Illiteracy       0.11  -0.44       1.00    -0.59   0.70   -0.66 -0.67  0.08
Life Exp        -0.07   0.34      -0.59     1.00  -0.78    0.58  0.26 -0.11
Murder           0.34  -0.23       0.70    -0.78   1.00   -0.49 -0.54  0.23
HS Grad         -0.10   0.62      -0.66     0.58  -0.49    1.00  0.37  0.33
Frost           -0.33   0.23      -0.67     0.26  -0.54    0.37  1.00  0.06
Area             0.02   0.36       0.08    -0.11   0.23    0.33  0.06  1.00
Sample Size
[1] 50
Probability values (Entries above the diagonal are adjusted for multiple tests.)
           Population Income Illiteracy Life Exp Murder HS Grad Frost Area
Population       0.00   1.00       1.00     1.00   0.23    1.00  0.25 1.00
Income           0.15   0.00       0.03     0.23   1.00    0.00  1.00 0.16
Illiteracy       0.46   0.00       0.00     0.00   0.00    0.00  0.00 1.00
Life Exp         0.64   0.02       0.00     0.00   0.00    0.00  0.79 1.00
Murder           0.01   0.11       0.00     0.00   0.00    0.01  0.00 1.00
HS Grad          0.50   0.00       0.00     0.00   0.00    0.00  0.16 0.25
Frost            0.02   0.11       0.00     0.07   0.00    0.01  0.00 1.00
Area             0.88   0.01       0.59     0.46   0.11    0.02  0.68 0.00

 To see confidence intervals of the correlations, print with the short=FALSE option