biostats - quiz 1

goal of statistics

learn about a large group by studying data that is collected from a smaller subset of that group

data

information collected from those involved in the study; it is used to draw conclusions about who/what is being studiedm

population

the entire, full group being studied; populations will vary in size, often large but do not have to be

examples of a population

all licensed doctors in PA, undergrads at DUQ, etc.

sample

a small subset of a population that is used to obtain data about the entire population; the data obtained that leads to an estimated conclusion about the population

parameter

a measurement that describes a fact or characteristic of a population

statistic

a measurement that describes a fact or characteristic of a sample

qualitative variables

categorical; used to separate data into different categories that are distinguishable by some non-numeric characteristic

used to classify or categorize; has limited computations (ex: ethnicity, eye color, etc.)

quantitative variables

have inherent numeric meaning; take numerical values for which arithmetic operations such as adding and averaging make sense

ex: height, weight, income, etc.

subcategories of quantitative variables

1. discrete variable

2. continuous variable

discrete variable

variables that are restricted to finite, countable values; characterized by gaps in the values that it can assume

ex: # of daily admissions to a local hospital

continuous variable

numerical values that can assume any value; variable that can take on any value in a specified interval

ex: amount of daily rainfall, gallons of gas pumped, etc.

representative sample

a sample should closely and accurately represent the population it was taken from; the characteristics of a sample should closely match the characteristics of a larger population

random sampling

individuals are randomly chosen from a population; gives the best change of obtaining a representative sample

observational studies

data collected/recorded only through observation; researchers observe and measure individuals, but do not modify them in any way

three types of observational studies

1. cross-sectional study

2. longitudinal (prospective) study

3. restrospective (case-control) study

cross-sectional study

data collected at one time point (ex: survey)

longitudinal (prospective) study

data collected over multiple time points; examines “trends” over time (ex: research question that asks how a behavior is training)

retrospective (case-control) study

data collected and reviewed from the past; researchers collect data from the past in order to learn more about the current status of a variable or topic

experiments

researchers apply modifications (treatments) to study participants and observe/analyze the impact

ex: clinical trials; include treatment and control groups

confounding variables

an individual/outside characteristic that impacts the validity of the experiment

ex: gender

ways to minimize confounding variables

1. blinding

2. blocking

3. randomization