Tall people earn more money--as much as $789 more a year in pay for every one in

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Tall people earn more money--as much as $789 more a year in pay for every one inch of height--than their shorter colleagues, according to a new study from the University of Florida and the University of North Carolina at Chapel-Hill. This pay differential based only on height is especially pronounced in management and sales positions.

Think $789 isn't all that much? Think again. Even after accounting for gender, weight, and age it means that someone who is 7 inches taller, say 6-feet vs. 5-foot-5, would be expected to earn $5,525 more annually. If you add this up over the course of a 30-year career and compound it, it's literally hundreds of thousands of dollars of earnings' advantage that a tall person enjoys.

"Height matters for career success," Florida researcher Timothy Judge wrote in the news release announcing the study he lead along with UNC's Daniel Cable. "These findings are troubling in that, with a few exceptions such as professional basketball, no one could argue that height is an essential ability required for job performance nor a bona fide occupational qualification."

The study: The two professors analyzed the results of four large-scale research studies, three of which had been conducted in the United States and one of which was done in Great Britain, that followed thousands of people from childhood to adulthood. Numerous details of their personal and professional lives were examined. The average height of Americans is 5 feet, 9 inches for men and 5 feet, 4 inches for women.

The results: People who were tall received higher subjective ratings of work performance, including supervisors' evaluations of how effective they were on the job. In addition, the objective measures of performance, including sales volume, were higher for tall people. Height is even more important than gender in determining salary, and its effect does not wane with age.

Why does height matter? Professors Judge and Cable speculate that being tall may have the effect of boosting employees' self-confidence, which might help them to be more successful in the workplace. In addition, others may ascribe more status and respect to a tall person. For example, tall sales people who are admired by customers may be seen as more persuasive leaders and may be able to negotiate more effectively. As a result, customers may be more likely to buy from them. "If height has the social status we think it does, it stands to reason that tall people would sell more cars because they're seen as a more authoritative source on the matter," Judge explained.

"If we have a bias against short people and that bias is not shared by other countries, we have placed ourselves at a competitive disadvantage," he said. "If we're giving great weight to an attribute like height that's irrelevant to performance on the job, then we're introducing error in our hiring and promotion decisions that causes inefficiencies in our economy."

The study findings will be published in the Journal of Applied Psychology.

Answer the following questions:

1) Was this an observational study or an experiment? Explain.

2) What are the observational units in this study?

3) The authors did a regression analysis for this study. Which variable mentioned was the explanatory variable and which variable is the response variable?

4) The authors reported the slope from their regression analysis, but not the y-intercept of the regression line. What is the slope? What does the slope mean in this context of this study?

5) Report the equation of the regression line (use a to represent the y-intercept).

6) The authors do not claim that the association between these two variables is a causal association. Why are they not able to draw this conclusion?

7) Do the authors mention any potential confounding variables? Can you think of any confounding variables not mentioned?

Explanation / Answer

1) Was this an observational study or an experiment? Explain.

This is an observational study because the research is conducted only using the simple observations based on the height and earning of the person. No any type of experiment is conducted for collection of the data for this research study.

2) What are the observational units in this study?

For this research study, the observational units are given as the height of the person and earning of the person.

3) The authors did a regression analysis for this study. Which variable mentioned was the explanatory variable and which variable is the response variable?

For this research study, the dependent variable or response variable for the given regression analysis is given as earning in $ while the independent variable or explanatory variable is given as the height of the persons in inches.

4) The authors reported the slope from their regression analysis, but not the y-intercept of the regression line. What is the slope? What does the slope mean in this context of this study?

The slope for the given regression equation is given as $789 which indicate the increment in pay for every inch of height. The value of slope is given as positive which indicate the positive relationship between the response variable earning and explanatory variable height of the person.

5) Report the equation of the regression line (use a to represent the y-intercept).

The required regression equation for the prediction of dependent variable or response variable earning of the person is given as below:

Earning = a + 789*Height in inch

Y = a + 789*X

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