Title has been removed


the science of data


the use of tables, graphs, and numerical measures to summarize data

Inferential Statistics

the use of sample data to learn about a population (could also say: the use of statistics to learn about parameters)


the entire set of items about which we desire information


values or outcomes of one or more variables for one or more observations


a characteristic that can have different values or outcomes


the set of information obtained for each item being "measured

Quantitative (QT)

values are numbers that result from a count or measure

Qualitative (QL)

values/outcomes that are usually words; classifications, attribute, categorical (no math)

Frequency Table

lists every outcome and the count for each

joint Outcome

the set of outcomes with respect to 2 or more variables


a table showing the frequency/count for each of all possible joint outcomes

Measures of Central Tendencies

tell us where the middle/center is; tell us what is typical/representative


average (x? = sample mean and = population mean)


middle value in an array


value that occurs most frequently

Measures of Variation

tell us how scattered/varied/dispersed the values are

T's Theorem

any data set will have at least/minimum of K% of its values in the intervals

z score

tells us how far a value is from the mean as measure in standard deviations


a value that lies out/away from the mass of values


the Kth percentile is the value such that at least K% of the values will be equal to or less thanProcess
1) array/sort the values in ascending order
2) the Kth percentile is the value in the K(n+1)th position where K is a decimal fraction
3) if K(n+1) an

Dot Plot

places a dot where the value occurs on a scaled axis


a bar chart for a quantitative variable