HW1. Needed in five hours. 2 pages. I need accurate answers

The next two columns refer to the deviation scores squared, since summing up deviation scores always equals zero and is of no use when determining variance.

Again, can you complete the cells for the last two employees?

Finally, the last column refers to the product of multiplying the deviation of X by the deviation of Y shown here as xy. Again, fill in the last two rows to check your understanding.

Now we are ready to calculate our correlation, r.

The following general categories indicate a quick way of interpreting a calculated r value (+ or –):

· 0.0 to 0.2: very weak to negligible correlation

· 0.2 to 0.4: weak, low correlation (not very significant)

· 0.4 to 0.7: moderate correlation

· 0.7 to 0.9: strong, high correlation

· 0.9 to 1.0: very strong correlation

Using the above guide the consulting psychologist would advise the human resource manager to conclude there is a weak relationship between years of employment and pay raises, and that the relationship is positive.

Caution must be exercised at this juncture as the relationship determined cannot as of yet be considered statistically significant.

Knowing that the situation included 10 individuals (N = 10: number of participants and degrees of freedom equal N – 2: two variables) to determine whether the results are statistically significant one must go to a "r" value table and determine what value is needed for statistical significance. In this case where the degrees of freedom are 8 (N – 2), the required r value at the probability level of 0.05 is +/- 0.549. The obtained r value in this case of + 0.36 is less than the required r value; therefore, the relationship is not statistically significant at the 0.05 probability level. Further, the consulting psychologist can conclude as well that the null hypothesis is accepted, and the relationship was most likely due to chance factors.

The same data cited above can be placed in the raw score formula, and the exact same r value will result. Note: Should an r value exceed +/– 1.0, the conclusion drawn is simply that a mathematical mistake has been made in the calculation process.