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CORRELATION MATRIXName:
Alternatively, you can compute the CDF or the p-value for the correlation coefficient (i.e., to see if the correlation coefficient is significantly different than zero). To see the formulas for the correlation coefficient and the CDF and p-values, enter
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the correlations are to be computed; <mat2> is a matrix where the resulting correlations are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context.
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the correlation CDF's are to be computed; <mat2> is a matrix where the resulting correlation CDF's are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context. This syntax computes the CDF of the correlation coefficient.
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the correlation p-value's are to be computed; <mat2> is a matrix where the resulting correlation p-values's are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context. This syntax computes the p-value of the correlation coefficient.
To specify a correlation matrix based on rows rather than columns, enter the command
To reset column based correlations, enter
To see the definitions for these, enter
2002/07: Support for Winsorized correlation, rank correlation, and biweight mid-correlation 2004/11: Support for Kendell tau correlation and for row based correlations 2012/06: Added support for cdf and p-values . This data is from page 202 of . . Peavy, Bremer, Varner, Hogben (1986), "OMNITAB 80: . An Interpretive System for Statistical and Numerical . Data Analysis," NBS Special Publication 701. . . Original source of the data is from . Draper and Smith (1981), "Applied Regression Analysis", . Wiley, p. 373. . dimension 40 columns . read matrix m 42.2 11.2 31.9 167.1 48.6 10.6 13.2 174.4 42.6 10.6 28.7 160.8 39.0 10.4 26.1 162.0 34.7 9.3 30.1 140.8 44.5 10.8 8.5 174.6 39.1 10.7 24.3 163.7 40.1 10.0 18.6 174.5 45.9 12.0 20.4 185.7 end of data . set write decimals 4 let corr = correlation matrix m print corrThe following output is generated. MATRIX CORR -- 4 ROWS -- 4 COLUMNS VARIABLES--CORR1 CORR2 CORR3 CORR4 1.0000 0.6837 -0.6160 0.8018 0.6837 1.0000 -0.1725 0.7680 -0.6160 -0.1725 1.0000 -0.6287 0.8018 0.7680 -0.6287 1.0000
Date created: 01/23/2013 |