> library(Hmisc)
> data(mtcars) > mtcars
데이터
mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
상관계수
> cor(mtcars$drat, mtcars$disp) [1] -0.7102139공분산> cov(mtcars$drat, mtcars$disp) [1] -47.06402
피어슨 상관계수
> rcorr(as.matrix(mtcars), type = "pearson") mpg cyl disp hp drat wt qsec vs am gear carb mpg 1.00 -0.85 -0.85 -0.78 0.68 -0.87 0.42 0.66 0.60 0.48 -0.55 cyl -0.85 1.00 0.90 0.83 -0.70 0.78 -0.59 -0.81 -0.52 -0.49 0.53 disp -0.85 0.90 1.00 0.79 -0.71 0.89 -0.43 -0.71 -0.59 -0.56 0.39 hp -0.78 0.83 0.79 1.00 -0.45 0.66 -0.71 -0.72 -0.24 -0.13 0.75 drat 0.68 -0.70 -0.71 -0.45 1.00 -0.71 0.09 0.44 0.71 0.70 -0.09 wt -0.87 0.78 0.89 0.66 -0.71 1.00 -0.17 -0.55 -0.69 -0.58 0.43 qsec 0.42 -0.59 -0.43 -0.71 0.09 -0.17 1.00 0.74 -0.23 -0.21 -0.66 vs 0.66 -0.81 -0.71 -0.72 0.44 -0.55 0.74 1.00 0.17 0.21 -0.57 am 0.60 -0.52 -0.59 -0.24 0.71 -0.69 -0.23 0.17 1.00 0.79 0.06 gear 0.48 -0.49 -0.56 -0.13 0.70 -0.58 -0.21 0.21 0.79 1.00 0.27 carb -0.55 0.53 0.39 0.75 -0.09 0.43 -0.66 -0.57 0.06 0.27 1.00 n= 32 P mpg cyl disp hp drat wt qsec vs am gear carb mpg 0.0000 0.0000 0.0000 0.0000 0.0000 0.0171 0.0000 0.0003 0.0054 0.0011 cyl 0.0000 0.0000 0.0000 0.0000 0.0000 0.0004 0.0000 0.0022 0.0042 0.0019 disp 0.0000 0.0000 0.0000 0.0000 0.0000 0.0131 0.0000 0.0004 0.0010 0.0253 hp 0.0000 0.0000 0.0000 0.0100 0.0000 0.0000 0.0000 0.1798 0.4930 0.0000 drat 0.0000 0.0000 0.0000 0.0100 0.0000 0.6196 0.0117 0.0000 0.0000 0.6212 wt 0.0000 0.0000 0.0000 0.0000 0.0000 0.3389 0.0010 0.0000 0.0005 0.0146 qsec 0.0171 0.0004 0.0131 0.0000 0.6196 0.3389 0.0000 0.2057 0.2425 0.0000 vs 0.0000 0.0000 0.0000 0.0000 0.0117 0.0010 0.0000 0.3570 0.2579 0.0007 am 0.0003 0.0022 0.0004 0.1798 0.0000 0.0000 0.2057 0.3570 0.0000 0.7545 gear 0.0054 0.0042 0.0010 0.4930 0.0000 0.0005 0.2425 0.2579 0.0000 0.1290 carb 0.0011 0.0019 0.0253 0.0000 0.6212 0.0146 0.0000 0.0007 0.7545 0.1290
pearson 자리에 spearman 을 넣고 돌리면 순위를 고려한 상관분석이 된다.
*상관계수 : 상관분석(Correlation Analysis)은 확률론과 통계학에서 두 변수간에 어떤 선형적 관계를 갖고 있는 지를 분석하는 방법이다
*공분산 : 확률론과 통계학에서, 공분산(共分散, 영어: covariance)은 2개의 확률변수의 상관정도를 나타내는 값이다
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