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### 37 Cards in this Set

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 FIELD TAGS WITHIN BRACKETS ABREVIATIONS FOR SEARCH CATEGORIES MeSH INDEXERS MUST: - Have at least a bacelor's degree in biomedical science - reading in one or more foreign language - special training in MEDLINE indexing STATISTICS ARE TO SAMPLES AS A _______ IS TO A POPULATION PARAMATER INDEPENDENT VARIABLE A TREATMENT OR INTERVENTION, PRECEDE THE DEPENDENT IN TIME DESCRIPTIVE STASTICS SUMMARIZE DATA BUT CAN NOT BE USED TO ________ TEST A HYPOTHESES VARIABILITY EXTENT VALUES ARE SPREAD ABOVE AND BELOW THE MIDDLE, a.k.a. DISPERSION MODE: MOST FREQUENT OCCURING VALUE MEDIAN: THE MIDDLE VALUE (NOT AVERAGE) LEVELS OF MEASUREMENT: NOIR NOMINAL, ORDINAL, INTERVAL, RATIO NOMINAL counting CODED BY NUMBER, NAME, OR LETTER NO ORDER ex: gender (male or female) Mode ORDINAL < > LIKE NOMINAL BUT ORDERED BY RANK - MORE OR LESS BUT NO TRUE VALUE OF VARIABILITY ex: military rank (lieutenant, captain...) Median INTERVAL + - MEASURES ORDERED WITH EQUAL INTERVALS - NO TRUE ZERO ex: fahrenheit symetrical Mean RATIO + - x / EQUAL INTERVALS - TRUE ZERO ex: ROM, lifting capacity (15kg, or 30kg) symetrical Mean Normal curve AREA 68.3% +/- 1SD 95.5% +/- 2SD S'(2) VARIANCE MEASURE OF SPREAD Z-SCORE Z=(x-u)/sigma x=raw score, u=mean, sigma=SD The number of SDs above or below the mean z-table portion of the area under the curve for different values of z INFERENTIAL STATISTICS DATA MAKE INFERECES ABOUT POPULATIONS, TAKE MANY MEANS AND THEN TAKE A MEAN OF THE MEANS SAMPLE MEAN IS AN ESTIMATE OR POINT ESTIMATE STANDARD ERROR OF MEAN = SEm lower the better SEm = SD/square root of (n) SEm is high when____ SD is large or sample is too small CONFIDENCE INTERVAL typical 95% range likely to contain population mean within 95% calculate CI range z-score @95% multiply by SEm +/- product to sample mean for limits SIZE OF CI _____ INDIRECT W/ SAMPLE SIZE SMALL SAMPLE - LARGE CI (BAD) null Hypothesis testing H(null) either accepted or rejected H(null) accepted no difference between two groups H(null) rejected if outside CI accept H1 - 95% that difference is true alpha error (type 1) reject H(null) = accept H1 (but false difference) beta error (type 2) accept H(null) = reject H1 (but true difference) as alpha <0.05 = type 1 decreases = type 2 increases Power = 1-beta probability of correctly rejecting a false H(null) standard power value 0.80 if value of difference is w/in CI then H(null) should not be rejected = no statistical difference t-test find whether the means of two groups are statiscally different one-tailed or two-tailed two is better because splits alpha between two tails t = difference between the group means/variability of the data big t = small p-value & statistically significant