1
BOIL 300 FUNDAMENTALS OF BIOSTATISTICS EXAM LATEST
UPDATE -2025/2026- 100+ QUESTIONS AND VERIFIED
ANSWERS ALL THE BEST
sampling error (or imprecision)
chance difference between a sample estimate and true value of corresponding
population parameter caused by random sampling
bias
systematic discrepancy between a sample estimate and corresponding population
parameter
random sample
subset of units from a population which had equal and independent chance at
selection
sample of convenience
subset of units from a population that are easily available to a researcher (i.e.
undesirable alternative to random sample)
volunteer bias
systematic discrepancy between a pool of volunteers and population to which
they belong (behaviour of subjects affects chance of being sampled)
variable
characteristic that differs among individuals, e.g. running speed, reproductive rate,
genotype; estimates
categorical (or attribute, or qualitative) variable
, 2
variable that describes a qualitative characteristic: nominal (no inherent order) or
ordinal (having order), e.g. survival, sex chromosome genotype, method of
disease transmission
numerical variable
variable that describes a quantitative characteristic: discrete or continuous, e.g.
body temperature, territory size, cigarette consumption rate
explanatory variable
(previously, independent variable), e.g. treatment variable
response variable
(previously, dependent variable), e.g. measured effect of treatment variable
frequency distribution
graph describing number of times each value of a (single) variable occurs in a
sample: relative (proportion) or absolute
estimation
process of inferring a population parameter from sample data
parameter
quantity describing a population: averages, proportions, measures of
variation/relationship = constant; truth
estimate (or statistic)
related quantity describing a population, calculated from a sample = variable;
approximation of truth, subject to error
population
set of all units of interest
sample
subset of units from a population
, 3
probability distribution
graph describing number of times each value of a variable occurs in a population,
often approximated by a normal distribution: discrete or continuous (probability
density, e.g. normal distribution); list of probabilities of all mutually exclusive
outcomes of a random trial
experimental study
"In an __________, the researcher assigns treatments of an explanatory variable
randomly to the participants, e.g. clinical trials. __________ can determine causal
relationships between variables."
observational study
"In an __________, the researcher has no control over which participants fall into
which treatment groups of an explanatory variable, e.g. studies of cigarette
smoking. __________ can only suggest associations."
relative frequency distribution
graph describing proportion of each value of a variable that occurs in a sample,
calculated as frequency divided by total number of observations
bar graph
graph displaying frequency distribution or relative frequency distribution of a
(single) categorical variable via height of rectangular bars
histogram
graph displaying frequency distribution or relative frequency distribution of a
(single) numerical variable via area of rectangular bars: uniform, bell-shaped,
asymmetric (skewed), bimodal
mode
highest peak interval of a frequency distribution, such as that of a histogram
contingency table
, 4
table displaying frequency of occurrence of all combinations of two or more
categorical variables, where columns = explanatory variable and rows = response
variable
grouped bar graph
graph displaying frequency distributions or relative frequency distributions of two
or more categorical variables via height of rectangular bars, grouped by categories
of explanatory variable
mosaic plot
graph displaying relative frequencies (or proportions) of occurrence of all
combinations or two or more categorical variables via area (i.e. height and width)
of rectangles
scatter plot
graph displaying observations of two numerical variables via points, where x-axis =
explanatory variable and y-axis = response variable
strip chart (or dot plot)
graph displaying observations of one numerical variable and one categorical
variable via "jittered" points, where explanatory variable is categorical
box plot
graph displaying a compact summary of frequency distributions of one numerical
variable and one categorical variable via lines and boxes, including: median
(midline), interquartile range (span of box), non-extreme (whiskers) or extreme
(dots beyond whiskers farther than 1.5X IQR) measurements
median
next most common descriptive statistic describing location of a frequency
distribution for a numerical variable: middle observation in a set of sample data
(measurement that partitions ordered measurements into two halves):
BOIL 300 FUNDAMENTALS OF BIOSTATISTICS EXAM LATEST
UPDATE -2025/2026- 100+ QUESTIONS AND VERIFIED
ANSWERS ALL THE BEST
sampling error (or imprecision)
chance difference between a sample estimate and true value of corresponding
population parameter caused by random sampling
bias
systematic discrepancy between a sample estimate and corresponding population
parameter
random sample
subset of units from a population which had equal and independent chance at
selection
sample of convenience
subset of units from a population that are easily available to a researcher (i.e.
undesirable alternative to random sample)
volunteer bias
systematic discrepancy between a pool of volunteers and population to which
they belong (behaviour of subjects affects chance of being sampled)
variable
characteristic that differs among individuals, e.g. running speed, reproductive rate,
genotype; estimates
categorical (or attribute, or qualitative) variable
, 2
variable that describes a qualitative characteristic: nominal (no inherent order) or
ordinal (having order), e.g. survival, sex chromosome genotype, method of
disease transmission
numerical variable
variable that describes a quantitative characteristic: discrete or continuous, e.g.
body temperature, territory size, cigarette consumption rate
explanatory variable
(previously, independent variable), e.g. treatment variable
response variable
(previously, dependent variable), e.g. measured effect of treatment variable
frequency distribution
graph describing number of times each value of a (single) variable occurs in a
sample: relative (proportion) or absolute
estimation
process of inferring a population parameter from sample data
parameter
quantity describing a population: averages, proportions, measures of
variation/relationship = constant; truth
estimate (or statistic)
related quantity describing a population, calculated from a sample = variable;
approximation of truth, subject to error
population
set of all units of interest
sample
subset of units from a population
, 3
probability distribution
graph describing number of times each value of a variable occurs in a population,
often approximated by a normal distribution: discrete or continuous (probability
density, e.g. normal distribution); list of probabilities of all mutually exclusive
outcomes of a random trial
experimental study
"In an __________, the researcher assigns treatments of an explanatory variable
randomly to the participants, e.g. clinical trials. __________ can determine causal
relationships between variables."
observational study
"In an __________, the researcher has no control over which participants fall into
which treatment groups of an explanatory variable, e.g. studies of cigarette
smoking. __________ can only suggest associations."
relative frequency distribution
graph describing proportion of each value of a variable that occurs in a sample,
calculated as frequency divided by total number of observations
bar graph
graph displaying frequency distribution or relative frequency distribution of a
(single) categorical variable via height of rectangular bars
histogram
graph displaying frequency distribution or relative frequency distribution of a
(single) numerical variable via area of rectangular bars: uniform, bell-shaped,
asymmetric (skewed), bimodal
mode
highest peak interval of a frequency distribution, such as that of a histogram
contingency table
, 4
table displaying frequency of occurrence of all combinations of two or more
categorical variables, where columns = explanatory variable and rows = response
variable
grouped bar graph
graph displaying frequency distributions or relative frequency distributions of two
or more categorical variables via height of rectangular bars, grouped by categories
of explanatory variable
mosaic plot
graph displaying relative frequencies (or proportions) of occurrence of all
combinations or two or more categorical variables via area (i.e. height and width)
of rectangles
scatter plot
graph displaying observations of two numerical variables via points, where x-axis =
explanatory variable and y-axis = response variable
strip chart (or dot plot)
graph displaying observations of one numerical variable and one categorical
variable via "jittered" points, where explanatory variable is categorical
box plot
graph displaying a compact summary of frequency distributions of one numerical
variable and one categorical variable via lines and boxes, including: median
(midline), interquartile range (span of box), non-extreme (whiskers) or extreme
(dots beyond whiskers farther than 1.5X IQR) measurements
median
next most common descriptive statistic describing location of a frequency
distribution for a numerical variable: middle observation in a set of sample data
(measurement that partitions ordered measurements into two halves):
