statistics data presentation

8/9/2019 STATISTICS Data Presentation

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STATISTICSBy: Johanne H. Rivas


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STATISTICS

Statistics is a mathematical sciencethat deals with the methods in the

collection, presentation, analysis andinterpretation, as well as drawingconclsions!generali"ations o# data.


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$S%& '( STATISTICS It can give precise prescription o# data.

It can predict )ehavior o# individals.

It can )e sed to test hypothesis.


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STATISTICA* +%TH'&S&escriptive statistics

Correlational statistics

In#erential statistics
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&%SCRITI-% STATISTICS&escriptive statistics descri)e the main #eatreso# a collection o# data antitatively. &escriptive

statistics are distingished #rom in#erentialstatistics /or indctive statistics0, in thatdescriptive statistics aim to smmari"e a dataset, rather than se the data to learn a)ot thepoplation that the data are thoght to

represent. This generally means that descriptivestatistics, nli1e in#erential statistics, are notdeveloped on the )asis o# pro)a)ility theory.


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C'RR%*ATI'2A*STATISTICS

In statistics, dependence re#ers to anystatistical relationship )etween two

random varia)les or two sets o# data.Correlation re#ers to any o# a )road classo# statistical relationships involvingdependence.


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I2(%R%2TIA* STATISTICS

In statistics, statistical in#erence is theprocess o# drawing conclsions #rom data

that are s)3ect to random variation. +ores)stantially, the terms statisticalin#erence, statistical indction andin#erential statistics are sed to descri)e

systems o# procedres that can )e sed todraw conclsions #rom datasets arising#rom systems a4ected )y randomvariation.


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HIST'R5 '( STATISTICSSome scholars pinpoint the origin o# statistics to6778, with the p)lication o# 2atral and olitical

')servations pon the Bills o# +ortality )y John9rant. %arly applications o# statistical thin1ingrevolved arond the needs o# states to )ase policyon demographic and economic data, hence its statetymology. The scope o# the discipline o# statistics)roadened in the early 6;th centry to inclde thecollection and analysis o# data in general. Today,statistics is widely employed in government,)siness, and the natral and social sciences.


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Its mathematical #ondations were laid in the

6


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'$*ATI'2 A2& SA+*%

A poplationis a set o# people or o)3ects yoare interested in #or a particlar stdy. It can )e a=niteor an in=nite poplation.

A sample is a collection o# elements ta1en #rompoplation. It can )e a )iasedor an n)iasedsample.

A randomsampleis a selected sample sch

that every mem)er o# a poplation has an ealchance o# )eing chosen.


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SA+*I29 T%CH2I@$%S

Samplingis selectinga parto# a poplation torepresentthe poplation.

Types:

pro)a)ility sampling

nonpro)a)ility sampling


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R'BABI*IT5 SA+*I29

In pro)a)ility sampling, each mem)er o# apoplation has a 1nown pro)a)ility o# )eingselected.

Types:

random sampling

strati=ed random sampling

clster sampling

systematic sampling


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2'2R'BABI*IT5 SA+*I29

In nonpro)a)ility sampling, samples are notchosen at random.

Types:

ota sampling

prposive sampling

accidental sampling


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ARA+%T%RS A2& STATISTICS

arameter a nm)er that represents or descri)esa poplation.

Statistic a nm)er that represents or descri)es asample.


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-ARIAB*%S A2& &ATA

-aria)le the characteristic or property o# a nit o#a poplation.

&ata a set o# o)served characteristic a)ot apoplation.

&ata set a collection o# data.

&ata point a single o)servation.

Raw data data that have not )een arranged oranaly"ed.

The data a)ot a poplation may )e antitativeor alitative.


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-ARIAB*%S I2 STATISTICS According to #nctional relationship:

dependent

independent According to continity o# vales:

discrete

continos

According to levels o# measrement:

nominal

ordinal

interval

ratio


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2'+I2A* SCA*%

In the nominal scale o# measrement,o)servations are groped into classes accordingto some attri)tes or properties.

%?ample:racial origin

eye color

Category

real nominal /real nominal dichotomos0arti=cial nominal


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'R&I2A* SCA*%

hen di4erent degrees o# a certain attri)te orproperty can )e detected or determined, then the

classi=cation is the ordinal scale. It shold )eemphasi"ed that the ordinal scale implies onlydegrees o# di4erence and does not implymeasra)le amonts o# these di4erences.

%?ample:military ran1


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I2T%R-A* SCA*%

I# an entity can )e measred in sch a way thatnot only the degree o# di4erence )t also theamont o# this di4erence has a meaning, then themeasrement #alls nder the interval scale.

%?ample:

scores in an e?am

temperatre in C


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RATI' SCA*%

In the ratio scale, not only addition ands)traction, )t also mltiplication and division o#o)servation vales are meaning#l.

%?ample:mass

electric charge


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Figure 1. Smmary o# scales o# measrement.


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9R'$%& (R%@$%2C5&ISTRIB$TI'2

Ale? measred the lengths o# leaves on the oa1 tree /tothe nearest cm0:

;,67,68,,6E,6,6,67,E,6F,6>,6,>,F,F,F,7,,6>,6F,6F,67,67,67,67,6


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2ow calclate an appro?imate grop si"e, )y dividingthe range)y how many grops yo wold li1e.

Then rond that grop si"e upto some simplevalue/li1e D instead o# 6.E8 or 5instead o# >.D70.

*et s say we want a)ot F grops. &ivide the range )yF:

6Then rond that p to >.

ic1 a starting vale that is less than or eal to thesmallest vale. Try to ma1e it a mltiple o# the gropsi"ei# yo can.

In or case a start vale o# ma1es the most sense.

/2ote: I# yo dont li1e the grops, then go )ac1 andchange the grop si"e or starting vale and try again.0


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6,6,6,>,>,F,F,F,7,,6>,6F,6F,67,67,67,67,6


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ST%+A2&*%A( *'T

Scores on a test o# physical coordination given to Dstdents:

7; E> FD ;8 76 7< ; D > E D

; 8

Figure 2. Stemand*ea# lot o# Scores on a Test o# hysicalCoordination.


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&'$B*%ST%+ *'TF. D

FK F

7K F < E ;

>

EK E

;. 8Figure . Stemand*ea# lot o# Scores on a Test o# hysicalCoordination.


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9RAHICA* R%R%S%2TATI'2

I% 9RAH

ICT'9RAH

BAR 9RAH

*I2% 9RAH

HIST'9RA+

(R%@$%2C5 '*59'2'9I-% *%SS THA2 C$R-%

'9I-% 9R%AT%R THA2 C$R-%


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I% 9RAH

Movie Freq. (f)

Comedy >

Action F

Romance 7&rama 6

Sci= >

2 G D

Ta)le 8

Favorite T!"e of Movie

Figure #$ (avorite Type o# +ovie


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ICT'9RAH

Figure 5. Pictograph of how many apples were sold atthe local shop over 4 months.


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&'T *'TS

Minutes Freq. (f)

7

6 D

D 8

8 F

> D

F F

7

<

E D

; 8

6

6D 6

2 G >

Ta)le >Minutes to %at Breakfast

Figure &. &ot plot o# mintes to eat)rea1#ast o# > people.


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BAR 9RAH

Fruit Freq. (f)

Apple 8F

'range 8

Banana 6

Liwi#rit DF

Ble)erry >

9rapes F

2 G 6>F

A survey of 145 people revealed their favorite fruit:

Ta)le FFavorite Fruit

Figure '. (avorite #rit o#6>F people.


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*I2% 9RAH

Days Freq. (f)

6 8

D >8 6D

> 6F

2 G 8>

You are learning facts about dogs, and each dayyou do a short test to see how good you are.hese are the results:

Ta)le 7Facts ( )ot Correct

Figure *. (acts I got correcta)ot dogs.


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HIST'9RA+

The #ollowing is the distri)tion o# the nm)er o#meals which 7 real state salespersons chargedas )siness e?penses in a given wee1:

Ta)le < +um,er of Meals of &- .eal State Sales"ersonsCharged

as Business %/"ensesNumer of Meals Freq. (f)

6 67

D 8 DF

> F 68

7 < >

E ; D


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Figure 0. 2m)er o# meals o# 7 real state salespersonscharged as )siness e?penses.


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(R%@$%2C5 '*59'2

$sing the data given )elow, constrct a morethan cmlative #reency ta)le and draw the#reency polygon, less than ogive and more thanogive.


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Mar!s


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*%SS THA2 '9I-%

Mar!s

"umu

lative

Frequ

ency


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9R%AT%R THA2 '9I-%

"umu

lative

Frequ

ency

Mar!s

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