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Statistics: Floor to ceiling effect, use of interval, normal

2.22 Would the data for number of murders by those convicted of the crime be an example of a floor or ceiling effect?

2.36. For each of the types of data described below, would you present individual data values or grouped data when creating a frequency distribution? Explain your anwser clearly. (a) eye color observed for 87 people (b) minutes used on a cell phone by 240 particpants (c) time to complete the Boston Marathon for the nearly 22,000 runners who participate (d) number of siblings for 64 college students.

2.4. Describe two ways that statisticians might use the word interval.

2.8. What is a normal distribution?

2.10. What are floor and ceiling effects?

2.12. Convert 817 out of 22,140 into a percentage. Now convert 4009 out of 22,140 into a percentage. What type of variable: (ordinal, nominal, or scale) are these data counts? What kind of variable are they as percentages?

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2.22 This would be a ceiling effect because a high proportion of the subjects studied would have the maximum score on the observed variable.

2.36 (a) Grouped because there are easily defined groups like 'green', blue', 'brown' etc. (b) Individual because it's not a relatively large sample and it would be difficult to define groups and every time ...