3. Biostatistics Flashcards
Define the 2 types of study data (broad) and their respective two categories.
Continuous data: logical values that increase/decrease by equal units (ie. HR, BP).
- Interval = has no impactful zero (ie. 0 Celsius just means freezing point of water)
- Ratio = has meaningful zero (ie. HR of 0 means no pulse, aka cardiac arrest)
Discrete data: categorical data (not on a continuous spectrum)
- Nomial = data sorted into arbitrary categories w/ names (ie. Male/female, yes/no)
- Ordinal = numerical ranked data, but difference between ranks is not equal (ie. 0-10 pain scale)
What three values are included in the “measures of central tendency”? Define each
MEAN: aka the average
MEDIAN: the middle value when numerical values are lined up lowest to highest
MODE: the value that occurs most frequently
What two values describe the spread of data? Define each
RANGE: the difference between the highest and lowest values
STANDARD DEVIATION: indicates dispersal from the mean, higher SD = more dispersed data
What is a Gaussian distribution?
When large sets of continuous data form a symmetrical, bell-shaped curve. Two-tailed
Mean, median and mode are all the SAME value
68% of the data falls within 1 standard deviation
Described “skewed data”? What kind of sample set and value is likely to cause this?
Skewed = non-symmetrical data
Usually occurs when sample size is SMALL, often with OUTLIERS
What is the null hypothesis (H0)?
The statement that there is NO significant difference between two study groups. AKA the statement researchers are trying to disprove.
What is the name for the opposite hypothesis from the null hypothesis?
The alternative hypothesis = states there is a significant difference between two study groups, and is what researchers are trying to PROVE.
What is the alpha level? What is it most commonly set to?
The maximum permissible error margin
Commonly set to 0.05 (5%)
How does the alpha value differ from the P value?
Alpha value is a permissible limit of error set BEFORE the study
P value is calculated AFTER with the data, and COMPARED to the alpha
AKA, if P < 0.05, the null hypothesis is rejected and the results are significant
What is the confidence interval? How is it calculated?
Represents the precision of the results along w the significance of the data (like the P value)
CI = 1- alpha [aka if alpha is set to 0.05, the CI will be 0.95 or 95%]
*NOTE: When using 95% CI for…
DIFFERENCE data = if the CI includes ZERO the data is non-significant
RELATIVE RISK, OR, HR = if the CI includes ONE the data is non-significant
What is the difference between Type I and Type II errors?
TYPE I: False positive (alpha error)
- When alpha is 0.05 and P value is falsely reported as <0.05, thereby falsely disproving the null
TYPE II: False negative (beta error)
- Occurs when null is accepted when it should have been rejected
What is study POWER?
Power = the probability that the null will be rejected CORRECTLY. Power to avoid type 2 error.
Aka = 1 - (beta)
Determined by the # of outcome values collected, difference in outcome rates, and alpha level.
Relative risk equation
(X/total subjects in TREATMENT group)
RR = ———————————————————
(Y/total subjects in CONTROL group)
Relative risk reduction equation
1 - RR
OR
(% risk in control - % risk in treatment)
——————————————————
(% risk in control)
Absolute risk reduction equation
ARR = (% risk in control group) - (% risk in treatment group)