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Hoop Ratings
Examine the correspondence between the team ratings of collegiate basketball polls. Adverse Reactions 1
Test whether adverse reaction times differ significantly between two groups of patients. Adverse Reactions 2
Test whether adverse reaction times differ significantly between two groups of patients. |
Hoop Ratings: Problem |
The Basketball data set contains the preseason ratings of collegiate basketball teams for the 1985-86 season as given by ten media outlets. Use the Spearman correlation to give an assessment of the relationship between the team ratings by the UPI and AP polls. |
Lee Creighton (modified by Paris Faison)
SAS Institute
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Hoop Ratings: Sample Data | |
The Basketball data set gives the pre-season ratings of collegiate basketball teams for the 1985-86 season as given by ten media outlets. These are the variables in the data set: Name | Type | Description | | school | char | university team represents | | CSN | num | team rating by CSN | | Durham Sun | num | team rating by Durham Sun | | Durham Herald | num | team rating by Durham Herald | | Washington Post | num | team rating by Washington Post | | USA Today | num | team rating by USA Today | | Sports Magazine | num | team rating by Sports Magazine | | In Sport | num | team rating by In Sport | | UPI | num | team rating by UPI | | AP | num | team rating by AP | | Sports Illustrated | num | team rating by Sports Illustrated | |
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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. |
Hoop Ratings: Solution |
The value of the Spearman correlation coefficient is 0.95. This indicates that there is a very strong positive association between the ratings by the UPI and AP polls. So, we can say that high team ratings by the UPI poll are associated with high ratings by the AP poll, and low ratings are by the UPI are associated with low ratings by the AP.
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Physician Referrals 1: Problem |
A study was done to investigate the effect of hospice marketing visits on the change in number of referrals received from doctors. There were two types of visits (one accompanied by a physician, and one by the hospice staff only), and the change in referrals after one month (change1) and after three months (change3) were recorded, along with other variables.
Use the median test to determine whether the change in referrals after one month differs for the two types of visits. |
SAS Institute Inc.
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Physician Referrals 1: Sample Data | |
The Hospice data set contains data about referrals received from physicians after a visit by a hospice marketing nurse. These are the variables in the data set: Name | Type | Description | | ID | num | physician ID | | Practice | char | type of practice | | Date | char | date of visit | | Change3 | num | change in number of referrals after 3 months | | Change1 | num | change in number of referrals after one month | | Visit | char | type of visit | |
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Source of Data
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This data is sample data from SAS Institute Inc. |
Physician Referrals 1: Solution |
You’re testing the following hypotheses: Ho: no difference in change in referrals after three months between the two types of visits against the two-sided alternative Ha: there is a difference in change in referrals after
three months between the two types of visits The median test statistic is M = 6.9375, with a standardized value of z = 0.4275. The p-value for the two-sided test is 0.6690, which fails to give sufficient evidence against the null hypothesis. So, we cannot conclude that there is a difference in the change in referrals after one month between the two types of visits. |
Adverse Reactions 1: Problem |
The manufacturers of a medication were concerned about adverse reactions in patients that were treated with their drug. Data on adverse reactions was gathered and stored in a file. The duration of the adverse reaction was recorded as the dependent variable. Patients were either given a placebo or received the standard drug regimen.
Test whether there is a significant difference in adverse reaction times between the two groups using the nonparametric median test. Use a significance level of α = 0.10. |
Lee Creighton (modified by Paris Faison)
SAS Institute Inc.
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Adverse Reactions 1: Sample Data | |
The Adverser data set contains information on patients and their adverse reactions to a drug treatment. These are the variables in the data set: Name | Type | Description | | PATIENT_ID | num | patient identification number | | TREATMENT_GROUP | char | treatment patient received (placebo or standard drug) | | TOTAL_DAILY_DOSE | num | daily dosage | | DAY_ON_DRUG | num | number of days patient was on treatment | | AGE | num | age | | SEX | char | sex | | WEIGHT | num | weight | | ADVERSE_REACTION | char | type of adverse reaction | | RACE | char | race | | ADR_SEVERITY | char | level of severity of adverse reaction | | RELATION_TO_DRUG | char | relation of adverse reaction to drug | | ADR_DURATION | char | duration of adverse reaction | |
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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. |
Adverse Reactions 1: Solution |
The results of the two-sample median test generated by the NPAR1WAY procedure in SAS show a p-value of 0.1132. This outcome is not significant at the α = 0.10 level (since p-value > 0.10). So we can conclude that the data does not provide strong enough evidence to suggest that there is a significant difference in adverse reaction times between the two treatment groups. |
Adverse Reactions 2: Problem |
The manufacturers of a medication were concerned about adverse reactions in patients that were treated with their drug. Data on adverse reactions was gathered and stored in a file. The duration of the adverse reaction was recorded as the dependent variable.
Patients were either given a placebo or received the standard drug regimen. Test whether there is a significant difference in adverse reaction times between the two groups using the nonparametric median test. Use a significance level of α = 0.10. ~nl~ |
Lee Creighton (modified by Paris Faison)
SAS Institute Inc.
Printer Friendly |
Adverse Reactions 2: Sample Data | |
The Adverser data set contains information on patients and their adverse reactions to a drug treatment. These are the variables in the data set: Name | Type | Description | | PATIENT_ID | num | patient identification number | | TREATMENT_GROUP | char | treatment patient received (placebo or standard drug) | | TOTAL_DAILY_DOSE | num | daily dosage | | DAY_ON_DRUG | num | number of days patient was on treatment | | AGE | num | age | | SEX | char | sex | | WEIGHT | num | weight | | ADVERSE_REACTION | char | type of adverse reaction | | RACE | char | race | | ADR_SEVERITY | char | level of severity of adverse reaction | | RELATION_TO_DRUG | char | relation of adverse reaction to drug | | ADR_DURATION | char | duration of adverse reaction | |
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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. |
Adverse Reactions 2: Solution |
The results of the two sample median test generated by the NPAR1WAY procedure in SAS shows a p-value of 0.1132. This outcome is not significant at the α = 0.10 level (since p-value > 0.10). So we can conclude that the data does not provide strong enough evidence to suggest that there is a significant difference in adverse reaction times between the two treatment groups. |
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