# EBM Exam 1

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The flashcards below were created by user Rx2013 on FreezingBlue Flashcards.

1. Sample
• must be representative of the entire population
• generizability
2. Random sampling
• evenly distributed patient characteristics
• equal chance of being in the study
3. Paired sample
each subject has a matching mate in the other group
4. independent sample
• subjects are not matched as pairs
• larger number of patients needed
5. Data types
• interval
• ratio
• ordinal
• nominal
6. Interval data
• continuous
• known, equal distance between each interval
• may contain negative numbers
• ex. temperature
7. Ratio data
• continuous
• known, equal distance between each interval
• non-arbitrary zero
• no negative numbers
• ex. age, wt, BG, BP, incidence rates of outcomes
8. Ordinal Data
• categorical
• ranked
• intervals not equal
• ex. pain scale, military rank
9. Nominal Data
• categorical
• cannot be ranked
• binomial or non-binomial
• binomial ex. mortality, gender
• non-binomial exp. eye color, hair color, ethnicity
10. statistical methods/test are described as being
parametric or non-parametric
11. When do you use parametric tests?
• data from sample results numerically describe a characteristic
• assumes normal distribution
• applies to most interval and ratio data
12. which are more powerful, parametric tests or non-parametric tests?
parametric tests
13. when do you use non-parametric tests?
• no assumption reguarding distribution
• applies to ordinal and nominal data
• can be applied to interval and ratio data when distribution is skewed
14. specific characteristic determining use of parametric/non-parametric tests
• type of data
• assumed distribution of data
• how many groups a study includes
15. parametric test examples
• student's t-test - 2 groups
• anova, ancova - >2 groups
16. non-parametric test examples
• chi square test
• fisher's exact test - smaller #
• mann-whitney U test
• Wilcoxin test
• Kruskal-wallis test
17. Null hypothesis
• theory about an outcome that a study is designed to test
• null = no difference between study groups
18. Alternate hypothesis
• opposite of null hypothesis
• there is a difference between study groups
19. alpha
level of significance
20. we usually classify something as statistically significant if it
falls below a certain level of significance
21. statistical & clinical significance
• may be statistically significant but not clinically important
• if it is not statistically significant it cannot be clinically important
22. p-value
• chosen level of significance
• usually p<0.05
• describes the probability that differences between 2 groups occured by chance
23. if p-value < alpha
• statistically significant
• reject null hypothesis
24. if p-value > alpha
• not statistically significant
• fail to reject null hypothesis
25. setting alpha establishes
probability of making a type I error
26. type I error
• incorrectly reject null hypothesis
• false positive
• say there is a difference when there isn't
27. setting Beta establishes
• probablility of making a type II error
• conventionally set at 0.2
28. Type II error
• incorrectly fail to reject the null hypothesis
• false negative
• say there is no difference when there may be one
• associates with too small sample population
• used in calculating power

### Card Set Information

 Author: Rx2013 ID: 132000 Filename: EBM Exam 1 Updated: 2012-01-31 17:04:58 Tags: Biostats1 Folders: Description: Biostats 1 Show Answers:

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