7. Chapter i5, Problem Timothy Judge and Daniel Cable examined the weight/salary

Question

7. Chapter i5, Problem Timothy Judge and Daniel Cable examined the weight/salary relationship for women and men and found a negative relationship for women but a positive relationship for men, suggesting that very different standards apply to mern than to women (Judge, T. A., & Cable, D. M. (2010). When it comes to pay, do the thin win? The effect of weight on pay for men and women. Journal of Applied Psychology, 96, 95-112, doi: 10.1037/a0020860] The following are data similar to those obtained for working men. Again, weight relative to height is coded in five categories from 1 - thinnest to 5 - heaviest. Income is recorded as thousands of dollars earned annually. Weight (X) Income (Y) 4 49 73 45 92 53 148 Compute the Pearson correlation. Use two decimal places for the ss and SP values, three for r. Ex2 SSx SSy SP Is the correlation statistically significant? Use a two-tailed test with .05.

Explanation / Answer

Here we will calculate the pearson correlation coefficient

SSx = x2 - (x)2/n = 90 - 242/ 8 = 18

SSy = y2 - (y)2/n = 75012 - 7042/8 = 13060

SSxy = xy - xy/n = 2393 - 24 * 704/8 = 281

Here SP = ( x - x)(y -) = SSxy = 281

Correlation coefficient r = SSxy / sqrt [SSxxSSyy] = 281/ sqrt (18 * 13060) = 281/ 484.85 = 0.5796

Here for alpha = 0.05,

rcritical = 0.707 for dF = 8 - 2 = 6

so here r < rcritical so correlation is not statistically significant.

Weight (X) Income (Y) X^2 Y^2 XY 4 156 16 24336 624 3 88 9 7744 264 5 49 25 2401 245 2 73 4 5329 146 1 45 1 2025 45 3 92 9 8464 276 1 53 1 2809 53 5 148 25 21904 740 24 704 90 75012 2393

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