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Arrivals
Determine whether on-time arrivals differ between months. Blood Pressure 1
Determine whether a medication was successful in reducing blood pressure. |
Arrivals: Problem |
The Department of Transportation recorded data that contains the percentage of airlines’ planes that arrived on time in 29 airports. Suppose you to examine the differences between March and June.
Perform a matched pairs test to determine whether there is a difference in on-time arrivals between the two months. Use a significance level of α = 0.05. |
Lee Creighton (modified by Paris Faison)
SAS Institute
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Arrivals: Sample Data | |
The On_time_arrivals data set gives information on the percentage of on-time arrivals for airplanes of 10 airlines for the months of March, June, and August in the year 1999. These are the variables in the data set: Name | Type | Description | | Airline | char | airplane airline | | March_1999 | num | percentage of airplanes that arrived on-time in March | | June_1999 | num | percentage of airplanes that arrived on-time in June | | August_1999 | num | percentage of airplanes that arrived on-time in August | |
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Source of Data
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Sall, J., Creighton, L., & Lehman, A. (2006). JMP Start Statistics, Third Edition. Cary, NC: SAS Institute Inc. |
Arrivals: Solution |
Using SAS Enterprise Guide, the p-value for the matched pairs test is found to be 0.0021, which is significant at the α = 0.05 level. Hence, we can conclude that there is a significant difference in on-time arrivals between the months of March and June.
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Blood Pressure 1: Problem |
To observe the effectiveness of a medication in reducing blood pressure, an experiment was conducted in which researchers collected data from a random sample of individuals who were considered to have high blood pressure. The diastolic blood pressure of these individuals was recorded, after which they were placed on the medication. One month later, their diastolic pressure was recorded again. Determine whether the data gives good evidence that the medication was effective in reducing blood pressure by carrying out a test of significance (at level α = 0.05), pairing the two blood pressure recordings for each subject. |
SAS Institute Inc.
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Blood Pressure 1: Sample Data | |
The Bloodpressure data set contains data from a random sample of individuals with high blood pressure. Variables include subject, age, an initial measurement of diastolic pressure, and a later measurement of diastolic pressure after one month of medication. These are the variables in the data set: Name | Type | Description | | Subject | char | subject code | | Age | num | subject’s age | | BaselineBP | num | subject’s baseline blood pressure | | NewBP | num | subject’s blood pressure one month after starting to take medication | |
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Source of Data
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This data is sample data from SAS Institute Inc. |
Blood Pressure 1: Solution |
The mean difference between the two blood pressure recordings is greater than zero, which indicates an overall reduction in blood pressure, on average. You’re testing the following hypotheses: Ho: μ = 0 versus Ha: μ > 0,
where μ is the mean difference in blood pressure (BaselineBP - NewBP). The p-value is less than 0.0001, which is less than the .05 significance level. Hence, you can conclude that there is strong evidence to suggest that the medication was effective in reducing blood pressure. |
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