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BIOSTATISTICS FOR THE BIOLOGICAL AND HEALTH SCIENCES CERTIFICATION EVALUATION COMPLETE QUESTIONS AND SOLUTIONS GRADED APLUS

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BIOSTATISTICS FOR THE BIOLOGICAL AND HEALTH SCIENCES CERTIFICATION EVALUATION COMPLETE QUESTIONS AND SOLUTIONS GRADED APLUS

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BIOSTATISTICS FOR THE BIOLOGICAL AND
HEALTH SCIENCES CERTIFICATION
EVALUATION COMPLETE QUESTIONS AND
SOLUTIONS GRADED APLUS

●● Descriptive statistics
Answer: Summarizing data, organizing data, graphing, and describing
numeric information. Concerned with measures of central tendencies
and measures of dispersion, as well as their graphic presentation.


Refers to parameters used to describe the attributes of a set of data such
as mean, standard deviation, proportion, and rate.


●● Inferential statistics
Answer: Hypothesis testing and conclusion from the sample. Make
predictions or generalizations about a larger dataset based on a sample
from a smaller dataset.


●● Statistical methods are used to:
Answer: Measure and explain overall variation, differentiate between
random and meaningful variation, and facilitate the interpretation of data


●● Sampling

,Answer: Used to estimate or approximate the "real" or "true"
characteristics of the population under study.


●● Sample
Answer: A smaller group or subset of the population selected to
investigate the association between exposure and disease in the larger
population.


●● Vignette
Answer: Used to apply statistical notions to real-life scenarios.


●● Scales
Answer: Used to measure population characteristics.


●● Continuous variables
Answer: A measure that includes an infinite number of values. Described
with mean and standard deviation.


Examples: systolic blood pressure, height, BMI, age, temperature.


●● Discrete variables
Answer: Refers to only a few possible values, measured in categories or
classes. Described with a proportion or a percentage and rate.

, Examples: sex, race, marital status, skin color.


●● Ordinal variables
Answer: Refers to categorical measures with natural order. Described
using median or mode.


Examples: educational status, disease morbidity, SES.


●● Probability model
Answer: Used to infer the characteristics of the population from the
sample of inferential statistics, which attempts to answer the question as
to whether the observed difference is a result of "chance."


●● Accuracy
Answer: How close the estimate is to the true value. The ability of a
measurement to be correct, on average.


●● Bias
Answer: The systematic or differential error in an estimate.


●● Selection bias

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