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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