32 Questions
Which type of error is caused by variations that can distort data in one direction and introduce bias?
Systematic error
Which type of variable is characterized by a defined, continuous measurement scale?
Quantitative Characteristic
What is the possible cause of variation in Clinical Medicine related to the presence or absence of disease?
Presence or absence of disease
Which type of characteristic is described by features and words rather than numbers?
Qualitative Characteristic
Which type of variable is based on measurement scales or rank orders and assigns numbers that have a coherent meaning?
Quantitative Characteristic
What type of variable are naming or categoric variables not based on measurement scales or rank orders?
Nominal variables
Which of the following is an example of a dichotomous variable?
Gender (male/female)
What type of variable is skin color?
Nominal
In which type of variable does 0 degrees indicate absolute zero?
Ratio
Which of the following is an example of a ratio variable?
Height
What type of variable is satisfaction with care (e.g. very satisfied, fairly satisfied)?
Ordinal
Which type of variable shares characteristics of both discrete and continuous variables?
Risk and Proportions
What type of variable is blood pressure (systolic & diastolic)?
Continuous
Which type of variable is occupation?
Nominal
What type of variable is the scale of 0-10 for pain, with 0 for no pain and 10 for worst imaginable pain?
Ordinal
Which type of variable does satisfaction with care and amount of swelling in a patient’s legs illustrate?
Ordinal
Quantitative Characteristic (Quantitative data) is characterized using a defined, continuous measurement scale. For example, ______ & ______ blood pressure, Serum sodium level
Systolic, Diastolic
Systematic error is caused by variations that can distort data in one direction and can introduce ______. For example, weighing patients while wearing shoes
bias
Nominal variables are naming or categoric variables that are not based on measurement scales or rank orders. Numbers assigned to nominal variables are merely numerical names but size of the number has no ______ meaning
coherent
Qualitative Characteristic (Qualitative data) is described by features, words rather than ______
numbers
Random error is caused by random variation, slight, inevitable inaccuracies in measurement and does not introduce ______. For example, Blood pressure
bias
Possible causes of variation in Clinical Medicine include Biological differences, Presence or absence of disease, Stages or extent of disease, Different conditions of measurement, Different techniques of measurement, Measurement error, ______ variation
Random
Blood groups, Occupation, Food groups, Skin color are examples of ______ variables
Nominal
Variables with only two levels, such as Normal/Abnormal, Male/Female, Well/Sick, Living/Dead, are known as ______ variables
Dichotomous
Data characterized in terms of three or more qualitative values that have a clearly implied direction from better to worse are called ______ variables
Ordinal
Measurable data on continuous measurement scales that show the position of different observations relative to each other and the extent to which one observation differs from another are known as ______ variables
Continuous
Variables derived from a continuous scale with a true 0 point are referred to as ______ variables
Ratio
Variables that share some characteristics of both discrete and continuous variables, created by ratio of counts in the numerator to counts in the denominator, are known as ______ variables
Risk and Proportions
The conditional probability of an event (e.g. death or disease) in a defined population in a definite period is an example of higher ______
Risk
Temperature in Kelvin is an example of a ______ variable
Ratio
Gender (Male/Female) is an example of a ______ variable
Dichotomous
Blood pressure (Systolic & Diastolic) is an example of a ______ variable
Continuous
Explore the concept of variation and distribution in clinical medicine, including possible causes of variation such as biological differences, disease presence or absence, stages of disease, measurement conditions, techniques, and errors. Learn about systematic and random errors in data measurement.
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