← Epi - Test 1 Test
5 Written Questions
5 Matching Questions
- Regression to the Mean
- Gausian Curve
- John Snow
- Baye's Theorem of Conditional Probabilities
- a Normal distribution curve. based in statistical theory, describes the frequency distribution of repeated measurements of the same physical object by the same measurement.
- b A population group unified by a specific common characteristic, such as age, and subsequently treated as a statistical unit.
- c Did study of cholera
- d The more sensitive a test is, the better will be its NPV. The more specific a test it, the better will be its PPV.
- e "Patients selected because they represent an extreme value in a distribution can be expected, on average, to have less extreme values on subsequent measurements..This occurs for purely statistical reasons, not because the patients have necessarily improved." This is the reasoning behind repeating lab tests: "Subsequent values are likely to be more accurate estimates of the true value." p. 32
5 Multiple Choice Questions
- "the study of disease occurrence in human populations" p. 3
- 11,700. Of these 11,700 known to have HIV, ~4,500 have AIDS. (This number with AIDS will probably not be asked since the term AIDS is somewhat subjective. The viral load limit that a person must have to be considered suffering from AIDS has been lowered in recent years.)
- variables describing a possible effect p. 5
- (Dr. Wheat) author? journal?....i think...Kerr White New England Journal of Medicine, Nov. 2, 1961 "Ecology of Medical Care"
5 True/False Questions
Posttest Probability → The probability of disease after the test result is known.
Sensitivity → Proportion of people without the disease who have a negative test = true negatives/ (true negatives + false positives) p. 39
Number of People Living in the US with HIV. → 500,000-1,000,000
What is the leading cause of preventable death in the US? → ...300,000,000
Types of Prevention:
Secondary Prevention → Def: Early detection of existing disease to reduce severity and complications
Ex. Screening for cancer