repl.txt (3281B)
1 2 {{alias}}( x, y[, options] ) 3 Computes a Pearson product-moment correlation test between paired samples. 4 5 By default, the function performs a t-test for the null hypothesis that the 6 data in arrays or typed arrays `x` and `y` is not correlated. A test against 7 a different population correlation can be carried out by supplying the `rho` 8 option. In this case, a test using the Fisher's z transform is conducted. 9 10 The returned object comes with a `.print()` method which when invoked will 11 print a formatted output of the results of the hypothesis test. 12 13 Parameters 14 ---------- 15 x: Array<number> 16 First data array. 17 18 y: Array<number> 19 Second data array. 20 21 options: Object (optional) 22 Options. 23 24 options.alpha: number (optional) 25 Nnumber in the interval `[0,1]` giving the significance level of the 26 hypothesis test. Default: `0.05`. 27 28 options.alternative: string (optional) 29 Either `two-sided`, `less` or `greater`. Indicates whether the 30 alternative hypothesis is that `x` has a larger mean than `y` 31 (`greater`), `x` has a smaller mean than `y` (`less`) or the means are 32 the same (`two-sided`). Default: `'two-sided'`. 33 34 options.rho: number (optional) 35 Number denoting the correlation under the null hypothesis. 36 Default: `0`. 37 38 Returns 39 ------- 40 out: Object 41 Test result object. 42 43 out.alpha: number 44 Used significance level. 45 46 out.rejected: boolean 47 Test decision. 48 49 out.pValue: number 50 p-value of the test. 51 52 out.statistic: number 53 Value of test statistic. 54 55 out.ci: Array<number> 56 1-alpha confidence interval for the Pearson product-moment correlation 57 coefficient. The confidence interval is calculated using Fisher's 58 z-transform. 59 60 out.nullValue: number 61 Assumed correlation under H0 (equal to the supplied `rho` option). 62 63 out.alternative: string 64 Alternative hypothesis (`two-sided`, `less` or `greater`). 65 66 out.method: string 67 Name of test. 68 69 out.print: Function 70 Function to print formatted output. 71 72 Examples 73 -------- 74 > var rho = 0.5; 75 > var x = new Array( 300 ); 76 > var y = new Array( 300 ); 77 > for ( var i = 0; i < 300; i++ ) { 78 ... x[ i ] = {{alias:@stdlib/random/base/normal}}( 0.0, 1.0 ); 79 ... y[ i ] = ( rho * x[ i ] ) + {{alias:@stdlib/random/base/normal}}( 0.0, 80 ... {{alias:@stdlib/math/base/special/sqrt}}( 1.0 - (rho*rho) ) ); 81 ... } 82 > var out = {{alias}}( x, y ) 83 { 84 alpha: 0.05, 85 rejected: true, 86 pValue: 0, 87 statistic: 10.115805615994121, 88 ci: [ 0.4161679018930295, 0.5853122968949995 ], 89 alternative: 'two-sided', 90 method: 't-test for Pearson correlation coefficient', 91 nullValue: 0, 92 pcorr: 0.505582072355616, 93 } 94 95 // Print output: 96 > var table = out.print() 97 t-test for Pearson correlation coefficient 98 99 Alternative hypothesis: True correlation coefficient is not equal to 0 100 101 pValue: 0 102 statistic: 9.2106 103 95% confidence interval: [0.3776,0.5544] 104 105 Test Decision: Reject null in favor of alternative at 5% significance level 106 107 See Also 108 -------- 109