## Glossary of Biostats Chapter One

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- data
- observations (such as measurements, genders, survey responses) that have been collected

- statistics
- a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on the data

- population
- 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

- census
- collection of data from every member of the population

- sample
- subcollection of members selected from part of a population

- parameter
- measurement describing some characteristic of a population

- statistic
- 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

- experiment
- 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)

- confounding
- 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)