Research Module Flashcards
(60 cards)
What is the definition of epidemiology?
The quantitative study of the distribution, determinants, and control of health problems in human populations.
Who is known as the “father of epidemiology” and why?
John Snow—he linked cholera outbreaks to a contaminated water pump on Broad Street, ending the epidemic.
What are the three main aims of epidemiology?
(1) Describe disease distribution, (2) Identify etiological factors, (3) Provide data for planning and evaluating services.
What is a sample in epidemiology?
A selected group meant to represent the larger population.
Define simple random sampling.
Every individual in the population has an equal chance of being selected.
What is stratified random sampling?
The population is divided into subgroups (e.g., age/gender), and random samples are drawn from each.
What is cluster sampling?
Groups (not individuals) are randomly selected, e.g., tribes or clinics.
What is convenience sampling?
Selecting participants who are easy to access, without ensuring representativeness.
What is snowball sampling?
Participants recruit others from their network—used for hard-to-reach populations like drug users.
Define selection bias.
Bias from differences in how participants are selected into the study.
Define information bias.
Systematic errors in measurement or data collection (e.g., recall or interviewer bias).
What is confounding bias?
A third variable distorts the true relationship between exposure and outcome.
What is meant by “central tendency”?
A measure of the center of a distribution—mean, median, or mode.
When is the median preferred over the mean?
When data are skewed or have outliers.
What is variance?
The average squared deviation from the mean—indicates data spread.
What is standard deviation?
The square root of variance—measures spread of individual data points around the mean.
What is the standard error of the mean?
An estimate of how much the sample mean is likely to differ from the population mean.
What is kurtosis?
A measure of how “fat” or “heavy” the tails of a distribution are.
What is skewness?
A measure of asymmetry in the distribution.
What is a null hypothesis (H₀)?
A statement that there is no difference or association—assumed true until disproven.
What is an alternative hypothesis (H₁)?
The hypothesis that there is a real difference or association.
What is a p-value?
The probability of obtaining the observed result if the null hypothesis is true.
What does it mean if p < 0.05?
The result is statistically significant; we reject the null hypothesis.
What is a Type I error (α)?
False positive—rejecting the null when it is actually true.