A somewhat empty-headed I/T executive believes her programming staff will fix more software problems if she offers free coffee throughout the work day.  To test the hypothesis, she selects 60 programmers at random and tracks the number of software problems they fix during a 5-day period.  Following that, she institutes the free coffee program for these employees, then again measures how many problems they fix during that week.  The number of problems each programmer fixes are significantly correlated before and after the free coffee offering, r = .83.  The means and SDs are as follows:   M before = 38.7 M after = 40 SD before=  7.24 SD after =  7.12   Is the I/T exec’s hypothesis supported at α = .05?  Explain in laypersons’ terms.

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A somewhat empty-headed I/T executive believes her programming staff will fix more software problems if she offers free coffee throughout the work day.  To test the hypothesis, she selects 60 programmers at random and tracks the number of software problems they fix during a 5-day period.  Following that, she institutes the free coffee program for these employees, then again measures how many problems they fix during that week.  The number of problems each programmer fixes are significantly correlated before and after the free coffee offering, r = .83.  The means and SDs are as follows:

 

M before = 38.7 M after = 40

SD before=  7.24 SD after =  7.12

 

Is the I/T exec’s hypothesis supported at α = .05?  Explain in laypersons’ terms.

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