Data and Biostatistics

biostatistics

application of statistics in public health

population

entire set of people or thing that we are interested in applying our results to

target population

the group you ideally want to generalize results to

source population

specific individuals from which a representative sample will be drawn from

study population

the group you can get access to

sample

subset of the population that we collect data on to make inferences to the population

convenience sample

data collected from population members who are conveniently able to participate in a study

null hypothesis

no effect or difference between groups

alternative hypothesis

there is an effect or difference between groups

p-value

probability of obtaining a result as or more extreme than the one observed if null hypothesis is true

disadvantages of p-value

• poor measure of size of an effect

• mixes estimates of effect and uncertainty

• strongly determined by sample size

• has no practical meaning

confidence interval

includes the true value of a parameter in a given proportion of samples

self-selection bias

when individuals volunteer to participate, it often leads to the overrepresentation of a certain population

recall bias

participants do not accurately remember a past event or experience or leave out details when reporting about them

healthy user bias

subjects who are already healthy are more likely to participate in a study

publication bias

studies with positive/interesting findings are published more often than studies with negative findings

correlation

association b/w two variables