Part1 Flashcards
Ratio Data
Has 0s
Interval Data
Has no natural 0s
Discrete Data
The underlying variable assumes different numerical values, but the set of possible values is restricted to a specific list of numbers (like the number of books in a library)
Nominal Data
The underlying variable assumes different categorical values and these values have no specific ordering (like colors and shapes)
Binary Data
Nominal data for which there are only two categories (like true/false)
Ordinal Data
Underlying variable assumes different categorical values and these values have a specific ordering (like age group categories)
Ranked Data
The underlying variable assumes different numeric values or ordered categorical values, but these values are replaced by an integer to rank it (like places someone finishes in a race)
Continuous data
The underlying variable assumes different numeric values and the set consists of numbers on a continuum (like weight and height).
Frequency
Number of observations in an interval
Relative Frequency
The proportion of observations in each category
Cumulative relative frequency
the proportion of observations that are less than or equal to the upper endpoint of the interval
Q1
25th percentile, first or lower quartile
Q2
50th percentile, second quartile or median
Q3
75th percentile, 3rd or upper quartile
IQR
Interquartile range, Q3-Q1
Skewed Right
If the majority of the histogram is on the left and the whiskers trail to the right
Central Tendency
Numbers reflect the center of the data set
Skewed left
If the majority of the histogram is on the right and whiskers trail to the left
Statistic
Numerical value describing a SAMPLE characteristic
Parameter
Numerical value describing a population characteristic
Measures of dispersion
Numbers designed to reflect the degree or spread of variability
Coefficient of Variation
The ratio of the standard deviation to the mean, times 100
