Statistics Test 1

Front 1

Statistics

Back 1

A quantitative process of gathering and analyzing data to make inferences. Form the Italian word Statista meaning of the state.

Front 2

Data (plural)

Back 2

Pieces of information

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Datum (singular)

Back 3

a single piece of information

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Quantitative

Back 4

inherently numeric

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Qualitative

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non-numeric

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Variable

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name of the data

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discrete

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counting; expressed only as whole numbers

Front 8

Continuous

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measuring; able to be expressed as any real number(s)

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Experimental Research

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requires an intrusive "treatment" and a control group

Front 10

Observational Research

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non-experimental: not intrusive: passive

Front 11

Population

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all possible data elements under consideration, as defined.
N= population size= number of elements in population.

Front 12

Sample

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any subset of the population.
n= sample size= number of elements in sample.

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Census

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Population = census

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What is the criteria for a statistically valid random sample?

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1. every element of the sample is also an element of population.
2. Every element of the population has an equal chance of being selected.

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Simple Random Sample

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best for small populations and samples
randInt>(1,N,n)

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Systematic Random Sample

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variant of sample method; best for large populations
use sample interval i= N/n (round up)
Select random start (btw 1-i, or 1-N)
beginning with random start, select every i-th element.

Front 17

Stratified Random Sample

Back 17

used if representation of subpopulations is desired or required

Front 18

Stratum

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homogeneous subpopulation
Population N= N1+N2+....

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Cluster Random Sample

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best for very large population with many strata
a. take a random sample of all strata= cluster.
b. take random subsample from each member of the cluster only.

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Array

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a preliminary informal listing of data collected: unordered or ordered.

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Table

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what, where, when, how many.

Front 22

Components of every table

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Title: what, where, when, how many.
2+ columns, with column headings
2-10 lines no more then 20

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Grouped data or frequency table

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1st column: numeric data, usually in groups/ classes
2nd column: frequency: number of occurrences per class

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Rules for constructing a grouped data/ frequency table:

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1. the first datum is in the first class; last datum is in the last class.
2. No data value is in more than one class; (no overlapping)
3. uniform class widths for all classes is recommended (not required)
4. closed interval format if data is discrete, open interval format if data is continuous.

Front 25

W= class width

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(max-min)/k (round up!)
k= # of recommended classes

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lower class limits (l.c.l.)

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1st value in each class

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upper class limits (u.c.l.)

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last value in each class

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lower class boundaries (u.c.b.)

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lowest possible value in each class

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upper class boundaries (u.c.b.)

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highest possible value in each class

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midpoints

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(l.c.l. + u.c.l.)/2

Front 31

Bar graph

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vertical or horizontal separated bars, categorical axis

Front 32

Pareto Chart

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vertical bar graph with descending separated or joined bars.

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Circle graph

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proportional wedge segments for each datum

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line graph

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chronological, points connected by line segments.

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histogram

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contiguous vertical bars, numeric axes

Front 36

Polygon

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same axes as histogram, consecutive, connected straight line segments.

Front 37

Central Measures

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averages, measure the typical or central value of datum

Front 38

Mode

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the observed average, the value that occurs most often

Front 39

Median

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the position average, requires data to be in order.

Front 40

Mean

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the calculated average

Front 41

Measure of dispersion/ variation

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measure the amount of variation among the data.

Front 42

Range

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R= the quick and dirty" measure of variation: R= max-min or R=H-?

Front 43

Standard Deviation

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Svx the required standard dispersion measure; based on mean.

Front 44

Standard deviation

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Sx= the required standard dispersion measure, based on mean.

Front 45

Variance:

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the estimated accumulated amount of variation from the mean. variance= sx
2

Front 46

Skewness

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the existence of a minority of atypical, extreme values in distribution of data, which may significantly affect the mean and all measures of dispersion, but not the meadian or mode.