14. Biostats Flashcards
2 types of continuous data
interval data and ratio data
Interval data definition and example
No meaningful zero (zero does not equal none)
Example: temperature scale (0 celcius does not mean no temp)
Ratio data definition and example
Meaningful zero (zero equals none)
Example: HR (0 BPM is cardiac arrest)
2 types of discrete data
nomial and ordinal
Nomial data definition and example
Subjects are sorted into arbitrary categories (names) , order of categories does not matter
Example: gender, ethnicity, martial status, mortality
Ordinal data defintion and example
Ranked and has a logical order
Example: pain scale
Note: ordinal scale categories do not increase by the same amount (pain scale 4 is not necessarily 2x more than pain scale 2)
In normal distributions, ___% of values fall within 1 standard deviation of the mean
68%
In normal distributions, ___% of the values fall within 2 standard deviations of the mean
95%
In normal distributions, 99.7% of the values fall within ___ standard deviations of the mean
3 SDs
More lower values in data set and outliers are high values, data is skewed to (left/right), aka (negative/positive) skew
Right, positive
More higher values in data set and outliers are low values, data is skewed to (left/right), aka (negative/positive) skew
Left, negative
T/F: the null hypothesis and alternative hypothesis are always complementary; when one is accepted, the other is rejected
True
Define null hypothesis
There is no statistically significant difference between groups
Alpha (error margin) is the threshold for rejecting the null hypothesis. In medical research, alpha is commonly set at ____
5% or 0.05
T/F: If the p-value is less than alpha, the null hypothesis is rejected
True
T/F: If the p-value is greater than alpha, the null hypothesis is rejected
False - if p-value is greater than alpha, the study failed to reject the null hypothesis and results are not statistically significant
If alpha is 0.05, the study reports ___% confidence intervals
95%
If p-value is <0.01, it means __% probability (confidence) that the conclusion is correct; less than __% change it’s not
99% confidence, 1% chance it’s not
When comparing difference data (means, based on subtraction), the result is statistically significant if the CI range does not include ___
zero
When comparing ratio data (relative risk, odds ratio, hazard ratio, based on division), the result is statistically significant if the CI range does not include ___
one
A (narrow/wide) CI range implies high precision and a (narrow/wide) CI range implies poor precision
narrow, wide
False positive is considered to be a type __ error (null hypothesis was rejected in error)
Type 1 error
False negative is considered to be type __ error (null hypothesis is accepted when it should have been rejected)
Type 2 error
Study __ is the probability that a test will reject the null hypothesis corrected (i.e. the power to avoid a type 2 error)
Study power
