╨╧рб▒с>■  &(■   %                                                                                                                                                                                                                                                                                                                                                                                                                                                ье┴3 Ё┐pjbjb^^ Ъh<h<p       lввввввв╥╥╥╥╥ ▐ ╥eъЎЎЎЎЎЎЎЎ"$$$$$$,O o|PвЎЎЎЎЎPvввЎЎЎvvvЎ.вЎвЎ"v╢─ввввЎ"vаvввъ 6═б╝╥╥$R eeыvыv├хSignificance of r The correlation coefficient, r, may be tested for statistical significance. Ho: The value of the correlation between X and Y (specify variables) in the population of (specify the population from which your sample was obtained) = 0.00. E.g.: The correlation between height and weight for males between the ages of 18 and 40 is 0.00. The correlation between sociability and number of friends for female college students is 0.00. Obtain a sample of size N and compute the sample r. (N is the number of paired scores, typically the number of people for whom you have measures on the X and Y variables.) You should also make a scattergram to determine the appropriateness of r for your data. Determine whether you can reject the Ho or whether you are unable to reject the Ho. Some computer programs will give you a p-value for your r. Excel will do this with its regression routine. Alternatively, you may compare the sample r with the critical value of r for the relevant degrees of freedom. For r, df = N - 2. Reject Ho if the absolute value of the computed r is equal to or greater than the tabled value. If it is not, you are unable to reject the Ho. Psychologists typically adopt an alpha of .05 for this decision. If you reject Ho, you might be have made an alpha error. The sample r might be a chance fluctuation from a population in which the r is 0.00 -- a sample so extreme that the sample r would occur only 5% of the time when the Ho is true. If you do not reject Ho, you might have made a beta error. The population value of r may be different from 0.00, but the sample r may not be large enough to allow you to reject Ho. Example of appropriate wording when you reject Ho: Female college students with high sociability scores tend to have more friends than those with low sociability scores (r (30) = .42, p < .05). Note: if the computed r with df = 30 had been .449 or more, then the p value would be shown as p < .01. Example of appropriate wording when you are unable to reject Ho; The association between sociability and number of friends for female college students was not statistically significant, r (30) = .28, p > .05. Note that the Ho is not given in these statements although an astute reader could determine it from the statements. Note also that the statement when you are unable to reject Ho should not imply an acceptance of the Ho. You should not conclude that there is no association between these variables. 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