Chapter 8 Flashcards
measurement of a single characteristic can vary.
variable
can result in many factors including genes, nutrition, environmental exposures, age, sex, and race.
biological differences
often account for the variations observed in medical data and include factors such as time of the day, ambient temperature or noise, and the presence of fatigue.
Ex Blood pressure is higher with anxiety or following exercise and lower after sleep.
different conditions of measurement
can produce different results.
Ex. A blood pressure measurement derived from the use of an intraarterial catheter may differ from a measurement derived from the use of an arm cuff.
different techniques of measurement
can also cause variation
Ex. Two different blood pressure cuffs of the same size may give different measurements.
measurement errors
types of variation can distort data systematically in one direction
Ex. Measuring and weighing patients while wearing shoes
systematic error
Inevitable inaccuracies in obtaining measurement.
random error
continuous measurement scale
quantitative characteristics
described by its features, generally in words
qualitative characteristics
Naming or categoric variables that are not based on measurement scales or rank order
nominal variables
Variables with only two levels
Dichotomous (binary) Variables
Data can be characterized in terms of the three or more qualitative values that have clearly implied direction from better to worse.
ordinal (ranked) variables
Data that is measured in continuous (dimensional) measurement scales.
Continuous (dimensional) variables
If a continuous scale has a true 0 point, the variables derived from it, it is where zero has a value
ratio variables
variables created by the ratio, and can be analyzed using the statistical method
risks and proportions as variables
Can be shown by creating a table that lists the values according to the frequency with which the value occurs.
frequency distribution
Distance between highest and lowest
range
obtained from actual data or sample
real distribution
calculated using assumptions about the population from which the sample are obtained
theoretical distribution
Bell-shaped curve are often used to represent the expected or theoretical distribution of the observations
normal distribution or gaussian distribution
look for the tendency of observation
measures of central tendency
Frequency distribution typically has a mode at more than one value
mode
It is middle observation when data has been arranged from lowest to highest
median
It is the average value or the sum of all the observed values
mean
seldom but helps define the concept of dispersion
mean of absolute deviation
The fundamental measure of dispersion in statistics that are based on the normal distribution
variance
Used to describe the amount of spread in the frequency distribution, it is the average deviation of the mean
standard deviation
Horizontal stretching of a frequency distribution to one side or the other, so that one tail of observation is longer and has more observations than the other tail
skewness
Horizontal stretching of a frequency distribution to one side or the other, so that one tail of observation is longer and has more observations than the other tail
skewness
characterized by a vertical stretching or flattening of the frequency distribution
kurtosis
When the data are observed, everything looks normal below the mean; a value exceeding
extreme values or outliers
