cork: The Cork Dataset

In ACSWR: A Companion Package for the Book "A Course in Statistics with R"

Description

Thickness of cork borings in four directions of North, South, East, and West are measured for 28 trees. The problem here is to examine if the bark deposit is same in all the directions.

Usage

data(cork)

Format

A data frame with 28 observations on the following 4 variables.

North

thickness of cork boring in the North direction

East

thickness of cork boring in the East direction

South

thickness of cork boring in the South direction

West

thickness of cork boring in the West direction

References

Rao, C. R. (1973). Linear Statistical Inference and Its Applications, 2e. J. Wiley.

Examples

data(cork)
corkcent <- cork*0
corkcent[,1] <- cork[,1]-mean(cork[,1])
corkcent[,2] <- cork[,2]-mean(cork[,2])
corkcent[,3] <- cork[,3]-mean(cork[,3])
corkcent[,4] <- cork[,4]-mean(cork[,4])
corkcentsvd <- svd(corkcent)
t(corkcentsvd$u)%*%corkcentsvd$u
t(corkcentsvd$v)%*%corkcentsvd$v
round(corkcentsvd$u %*% diag(corkcentsvd$d) %*% t(corkcentsvd$v),2)
round(corkcent,2)
corkcentsvd$d

Example output

              [,1]          [,2]          [,3]          [,4]
[1,]  1.000000e+00  1.040834e-17  6.938894e-17 -1.252254e-16
[2,]  1.040834e-17  1.000000e+00 -1.387779e-16  1.812786e-16
[3,]  6.938894e-17 -1.387779e-16  1.000000e+00 -1.301043e-16
[4,] -1.252254e-16  1.812786e-16 -1.301043e-16  1.000000e+00
              [,1]          [,2]          [,3]          [,4]
[1,]  1.000000e+00  0.000000e+00  5.551115e-17 -5.551115e-17
[2,]  0.000000e+00  1.000000e+00 -5.551115e-17  3.885781e-16
[3,]  5.551115e-17 -5.551115e-17  1.000000e+00 -1.387779e-16
[4,] -5.551115e-17  3.885781e-16 -1.387779e-16  1.000000e+00
        [,1]   [,2]   [,3]   [,4]
 [1,]  21.46  19.82  26.32  31.82
 [2,]   9.46   6.82  16.32  17.82
 [3,]   5.46  10.82  14.32  12.82
 [4,]  -9.54 -17.18 -13.68  -7.18
 [5,] -18.54 -14.18 -14.68  -9.18
 [6,] -20.54 -11.18 -15.68 -19.18
 [7,] -11.54  -7.18 -18.68 -18.18
 [8,]  -8.54  -3.18 -18.68 -20.18
 [9,] -13.54  -6.18 -18.68 -20.18
[10,] -17.54 -17.18 -22.68  -9.18
[11,] -18.54 -16.18 -15.68 -17.18
[12,]  12.46  -1.18  24.32  17.82
[13,]   3.46  -0.18  10.32   6.82
[14,]  -3.54   4.82   2.32  -2.18
[15,]  40.46  32.82  50.32  29.82
[16,]   5.46  21.82  -2.68   4.82
[17,]  28.46  18.82  20.32  15.82
[18,]  30.46  33.82  18.32  12.82
[19,]  27.46   8.82  17.32  14.82
[20,]  -4.54  -8.18 -12.68  -7.18
[21,] -11.54 -11.18 -15.68  -8.18
[22,] -18.54 -16.18 -19.68 -13.18
[23,]   9.46   3.82  17.32   8.82
[24,] -15.54  -9.18  -1.68  -6.18
[25,] -11.54 -10.18 -10.68 -14.18
[26,]  -0.54 -12.18 -12.68  -5.18
[27,]  -7.54  -9.18 -10.68   4.82
[28,]  -2.54   7.82   7.32  -2.18
    North   East  South   West
1   21.46  19.82  26.32  31.82
2    9.46   6.82  16.32  17.82
3    5.46  10.82  14.32  12.82
4   -9.54 -17.18 -13.68  -7.18
5  -18.54 -14.18 -14.68  -9.18
6  -20.54 -11.18 -15.68 -19.18
7  -11.54  -7.18 -18.68 -18.18
8   -8.54  -3.18 -18.68 -20.18
9  -13.54  -6.18 -18.68 -20.18
10 -17.54 -17.18 -22.68  -9.18
11 -18.54 -16.18 -15.68 -17.18
12  12.46  -1.18  24.32  17.82
13   3.46  -0.18  10.32   6.82
14  -3.54   4.82   2.32  -2.18
15  40.46  32.82  50.32  29.82
16   5.46  21.82  -2.68   4.82
17  28.46  18.82  20.32  15.82
18  30.46  33.82  18.32  12.82
19  27.46   8.82  17.32  14.82
20  -4.54  -8.18 -12.68  -7.18
21 -11.54 -11.18 -15.68  -8.18
22 -18.54 -16.18 -19.68 -13.18
23   9.46   3.82  17.32   8.82
24 -15.54  -9.18  -1.68  -6.18
25 -11.54 -10.18 -10.68 -14.18
26  -0.54 -12.18 -12.68  -5.18
27  -7.54  -9.18 -10.68   4.82
28  -2.54   7.82   7.32  -2.18
[1] 163.03355  40.17752  25.40940  22.16929

ACSWR documentation built on May 2, 2019, 6:53 a.m.