Glossary of Biostats Chapter One

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observations (such as measurements, genders, survey responses) that have been collected
a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on the data
complete collection of all elements (scores, people, measurents, and so on) to be studied, collection is complete in the sense that it includes all subjects to be studied
collection of data from every member of the population
subcollection of members selected from part of a population
measurement describing some characteristic of a population
measurement describbing some characteristic of a sample
quantitative data
consist of numbers representing counts of measurements
qualitative data
aka categorical, attribute-can be serperated into different categories tht are distinguished by some non-numeric characteristic
discrete data
result when the number of possible values is either a finite number or a "countable" number (0, 1, 2...)
continuous data
numerical-result from infinitely many possible calues that correspond to some continuous scale that covers a range of values without gaps, interruption or jumps
nominal level of measurement
characterized by data that consist of names, labels, or categories only, the data cannot be arrange in an ordering scheme
ordinal level of measurement
data that can be arranged in some order, but differences between data values cannot be determined or are meaningless
interval level of measurement
like the ordinal level, with the additional property that the difference between any two data values is meaningful, however data at this level do not have a natural zero starting point
ratio level of measurement
interval elvel with the additional property that there is also a natural zero starting point (where zero indicates that none of the quantity is present) and for values at this level, differences and ratios are both meaningful
voluntary response sample
self-selected sample-one in which the respondents themsleves decide whether to be included
observational study
observe and measure specific characteristics, but we don't attempt to modify the subjects being studied
apply some treatment and then proceed to observe its offects on the subjects
cross-sectional study
data are observed, measured, and collected at one point in time
retrospective study
case-control study-data are collected from the past by going back in time (through examination of records, interviews, and so on)
prospective study
longitudinal, cohort-data are collected in the future from groups sharing common factors (called cohorts)
occurs when effects of variables are somehow mixed so that the individual effects of the variables cannot be identified
random sample
members from the population are selected in such a way that each individual member has the same chance of being selected
simple random smaple
of size n subjects is selected in such a way that every possible sample of same size n has the same chance of being chosen
systematic sampling
randomly select a starting point and then select every kth element in the population
convenience sampling
collect results that are very easy (convenient) to get
stratified sampling
subdivide the population into at least two different subgroups (or strata) that share the same characteristics (such as gender or age bracket), then we draw a sample from each subgroup
cluster sampling
first divide the population area into sections (or clusters), then randomly select some of those clusters, and then choose all the members from those selected clusters
sampling error
the difference between a sample result and the true population result, such as an error results from change sample fluctuations
nonsampling error
occurs when the sample data are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective measure instrument, or recording the data incorrectly)

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