An adventure company runs two obstacle courses, Fundash and Coolsprint. The designer of the courses suspects that the mean completion time of Fundash is not equal to the mean completion time of Coolsprint. To test this, she selects 240 Fundash runners and 200 Coolsprint runners. (Consider these as random samples of the Fundash and Coolspring runners.) The 240 Fundash runners complete the course with a mean time of 76.7 minutes and a standard deviation of 5.2 minutes. The 200 Coolsprint runners complete the course with a mean time of 77.5 minutes and a standard deviation of 5.4 minutes. Assume that the population standard deviations of the completion times can be estimated to be the sample standard deviations, since the samples that are used to compute them are quite large. At the 0.05 level of significance, is there enough evidence to support the claim that the mean completion time, μ1 , of Fundash is not equal to the mean completion time, μ2 , of Coolsprint? Perform a two-tailed test. Then complete the parts below.
An adventure company runs two obstacle courses, Fundash and Coolsprint. The designer of the courses suspects that the
Fundash runners and
Coolsprint runners. (Consider these as random samples of the Fundash and Coolspring runners.) The
Fundash runners complete the course with a mean time of
minutes and a standard deviation of
minutes. The
Coolsprint runners complete the course with a mean time of
minutes and a standard deviation of
minutes. Assume that the population standard deviations of the completion times can be estimated to be the sample standard deviations, since the samples that are used to compute them are quite large. At the
level of significance, is there enough evidence to support the claim that the mean completion time,
, of Fundash is not equal to the mean completion time,
, of Coolsprint? Perform a two-tailed test. Then complete the parts below.
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