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Statistics

the science of data

Description

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)

Population

the entire set of items about which we desire information

Data/database/data

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

Variable

a characteristic that can have different values or outcomes

Observation

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

Crosstab

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

Mean

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

Median

middle value in an array

Mode

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

Outlier

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

Percentile

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

Histogram

a bar chart for a quantitative variable