If A Study Determines The Difference In Average Salary For Subpopulations

The average salary for subpopulations is the average of all salaries for people in a particular population. A study designed to determine the difference in average salary for subpopulations must first determine what constitutes a subpopulation, then collect data about those subpopulations, and finally analyze the data.

The study determined the difference in average salary for subpopulations by taking a sample of the population, then calculating and comparing the average salaries of those subpopulations.

A study was conducted to determine the average salary for subpopulations. The results were as follows:

Subpopulation Average Salary

1,000 $100,000

2,000 $110,000

3,000 $120,000

4,000 $130,000

If A Study Determines The Difference In Average Salary For Subpopulations

If a study determines the difference in average salary for subpopulations of mechanical engineers and civil engineers is NOT significant,

If a study determines the difference in average salary for subpopulations of mechanical engineers and civil engineers is NOT significant, then the subpopulations of mechanical and civil engineers are different salaries.

A problem where one subpopulation is compared to several other subpopulations in terms of means with the goal of estimating the smallest difference between the means commonly arises in biology, medicine, and many other scientific fields. A generalization of Strassburger, Bretz and Hochberg (2004 Strassburger, K., Bretz, F., and Hochberg, Y. (2004). Compatible confidence intervals for intersection union tests involving two hypotheses, Institute of Mathematical Statistics Lecture Notes-Monograph Series 47:129–142.[CrossRef]) approach for two comparisons is presented for cases with three and more comparisons. The method allows constructing an interval-estimator for the smallest mean difference, which is compatible with the Min test. An application to a fluency-disorder study is illustrated. Simulations confirmed adequate probability coverage for normally distributed outcomes for a number of designs.

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