Studied by 4 people
Qualitative Data
a name or a label, ex. The color of a ball (e.g., red, green, blue) or the breed of a dog (e.g., collie, shepherd, terrier)
Quantitative Variables
a number, ex. number of people in the city, number of students in a school
Discrete Variables
can’t take on any value between its minimum value and its maximum value, ex. 5, 6
Continuous Variables
can take on any value between its minimum value and its maximum value, ex. 5.5, 6.3
Univariate Data
working with one variable, ex. weight
Bivariate Data
working with two variables, ex. height and weight
Population
includes all elements from a set of data
Sample
one or more observations drawn from the population
Parameter
measurable characteristic of a population, ex. mean or standard deviation
Statistic
measurable characteristic of a sample
Simple Random Sampling
a technique used in statistics to select a sample from a larger population in a way that every individual or element has an equal chance of being chosen
Median
the middle value
Mean
average of all the values
Outlier
an extreme value that differs greatly from other values
Range
the difference between the largest and smallest values in a set of values
Interquartile Range (IQR)
the difference between the largest and smallest values in the middle 50% of a set of data
Variance
average squared deviation from the population mean
Standard Deviation
square root of the variance, statistical measure that shows how spread out or dispersed a set of data points are from the mean
Quartiles
divide a rank-ordered data set into four equal parts
Standard Score/z-Score
indication of how many standard deviations an element is away from the mean
Note 
Flashcard (335)