Basic Math 2010

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BASIC MATHEMATICS [S T A T I S T I C S]

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CONFESSION PAGE

We recognize this work is the result of our own except for quotation and a summary of

each of them we describe the source

Signature : ...................

Name : Che Nurul Azieana Binti Che Yang

Date : 16th April 2010 .

Signature : ...................................... ............

Name : Nor Atirah binti Mohd Rapingi

Date : 16th April 2010.

Signature : ...................................... .....

Name : Madhihah binti Nordin

Date : 16th April 2010.

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BASIC MATH

MATICS [S T A T I S T I C S]

N A E : HENURUL AZIEAN A BT HE YANG

I. .NUMBER : 9 7- -558

ATE OF BIRTH : 7TH E EMBER 99

PLA E OF BIRTH : KLUANG, JOHOR

A RESS : NO 4 , JLN SRI ANGI, TMN SULIANA, SIKAMAT 7 4

SEREMBAN,NEGERI SEMBILAN.

GROUP : PPISMP (M ATH )

TEL.NO : 3- 9 93

HOBBY : LISTENING TO MUSI

AMBITION : LE TURER

E UCATION : SEK.KEB.TAMAN PAROI JAYA,

SEK.MEN.KEB. ATO HJ.MOH RE ZA,

SEK.MEN.TEKNIK AMPANGAN

JOHORMATRICULATIONCOLLEGE

FATHERS NAME : CHE YANG BIN HJ.SAMSUDIN

OCCUPATION : RETIRED SOLDIER

MOTHERS NAME : NORMALA BT ZAINOL ABIDIN

OCCUPATION : HOUSE IFE

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BASIC MATHMATICS [S T A T I S T I C S]

NAME : NOR ATIRAH BINTI MOHDRAPINGI

I.C.NUMBER : 9 5 - -5 44

DATE OF BIRTH :TH

M AY 99

PLACE OF BIRTH : LANGKA I, KEDAH

ADDRESS : PS 4 , KAMPUNG PADANG KANDANG,MKM PADANGMATSIRAT,

7 ,LANGKA I, KEDAH


TEL.NO : 3- 3 494

HOBBY : ARCHERY

AMBITION : LECTURER

EDUCATION : SEK.KEB.KUALA TERIANG

SEK.MEN. AGAMA PERSEKUTUAN KAJANG

KUALA NERANGMARA MATRICULATIONCOLLEGE

UNIVERSITY MALAYA

FATHERS NAME : MOHDRAPINGI BIN YUSOF

OCCUPATION : TEACHER

MOTHERS NAME : HAPISHAH BINTI YOM

OCCUPATION : HOUSE IFE

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NAME : MADHIHAH BINTI NORDIN

I.C.NUMBER : 9 9 - 4- 3 8

DATE OF BIRTH :

t SEPTEMBER 99

PLACE OF BIRTH : KLUANG, JOHOR

ADDRESS : G- - , QUARTERS PERKHIDMATAN A AM,NO , JALAN

DUTAMAS 3, 5 48 ,KUALA LUMPUR.


TEL.NO : 7- 3 5

HOBBY : LISTENING TO MUSIC

AMBITION : LECTURER

EDUCATION : SEK RENCONVENT SENTUL

SEKMENCONVENT

SEKMEN SAINS SERI PUTERI

FATHERS NAME : NORDIN BIN YUSOF

OCCUPATION : PUBLIC ADMINISTRATOR

MOTHERS NAME : NOOR AZIZAH BINTI AHMAD

OCCUPATION : CUSTOMER SERVICE OFFICER IMR

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BASIC MATHEMATICS [S T A T I S T I C S]CONTENT

BIL CONTENT PAGES

CONFESSION PAGE

QUESTION

PROFILE

CONTENT

ACKNOWLEDGEMENT

INTRODUCTION

ANALYSIS

CONCLUSION

COLLABORATION FORM

APPENDICES

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ACKNOWLEDGEMENT

irst of all, we would like to thank God that after all the hardship that we need to face

up; we manage to complete the assignment in the time given by the topic of matrices.

We are really appreciated those who lend their hand, give fantastic idea and share

their fabulous opinion especially Madam Norehan, our Mathematics lecturer that always

guide us in order to complete this assignment. She always makes sure all of us are

understand what the task craved.

Besides that, we also would like to thank our precious parents and families that

always are with us in hardship or happy time and always support a nd give advice to ensure

all of us are not give up although there are many obstacles.

Credits also for our beloved friends that let us share the information and help each

other to make sure all of us made assignment that follow the instructions. Not forgo tten

each our group members that always give full commitment and cooperation.

So, we are really appreciating all the effort those who help us whether their name was

mentioned or not.

hank you.

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as a means of understanding complex social phenomena such as

crime rates,marriage rates,orsuicide rates.Charles S. Peirce ( 839--

9 4) f ormulated frequenters theories of estimation and hypothesis-

testing in ( 877-- 878) and ( 883), in which he introduced

"confidence". Peirce also introduced blinded, controlled randomi ed

experiments with a repeated measures design. Peirce invented an

optimal design forexperimentsongravity.

Thewordstatisticscaneitherbesingularorplural. In itssingular form,astatistic isa

quantity (such as a mean) calculated from a set of data, whereas statistics is the

mathematical sciencediscussed in thisarticle. Statisticsalways related to thegraph. Forexample,bargraph,histogram,piechart, frequencypolygonandhistogram.

In statistics, a histogram is agraphical display of tabular frequencies, shown as

adjacent rectangles. Each rectangle iserectedoveran interval,with anareaequal to the

frequencyof the interval. Theheight ofarectangle isalsoequal to the frequencydensityof

the interval, i.e. the frequencydividedby thewidth of the interval. The total areaof the

histogram isequal to thenumberofdata. A histogrammayalsobebasedon the relative

frequencies instead. It then shows what proportion of cases fall into each of several

categories (a formofdatabinning),and the total area thenequals . Thecategoriesare

usually specified as consecutive, non-overlapping intervals of some variable. The

categories (intervals) must beadjacent,andoftenarechosen tobeof thesamesi e, [1]but

not necessarilyso.

Histograms are used to plot density of data, and often for density estimation:

estimating the probabilitydensity functionof theunderlying variable. The total areaof a

histogram used for probability density is always normali ed to 1. If the lengths of the

intervalson thex-axisareall 1, thenahistogram is identical toa relative frequencyplot.

Analternative to thehistogram is kernel densityestimation,whichusesakernel tosmooth

samples. Thiswill construct asmoothprobabilitydensity function,whichwill ingeneral more

accuratelyreflect theunderlying variable. Thehistogram isoneof thesevenbasic toolsof

qualitycontrol.

Charles S. Peirce

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A barchart orbargraph isachart withrectangularbarswith lengthsproportional

to thevalues that theyrepresent. Thebarscanalsobeplottedhori ontally.

Barchartsareused forplottingdiscrete (or 'discontinuous') data i.e. datawhichhas

discretevaluesand isnot continuous. Someexamplesofdiscontinuousdata include 'shoe

si e' or 'eyecolour', forwhichyouwoulduseabarchart. Incontrast,someexamplesof

continuousdatawouldbe 'height' or'weight'. A barchart isveryuseful ifyouare t rying to

recordcertain informationwhetherit iscontinuousornot continuousdata.

DIAGRAM 1.0 : EXAMPLE OF HISTOGRAM

DIAGRAM 1.1 : EXAMPLE OF BAR CHART

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A pie chart (or a circle graph) is circular chart divided into sectors, illustrating

proportion. Inapiechart, the arc lengthofeachsector (andconsequently itscentral angle

andarea), isproportional to thequantity it represents. Together, thesectorscreatea full

disk. It isnamed for itsresemblance toapiewhichhasbeensliced. Theearliest knownpie

chart isgenerallycredited to illiam Playfair'sStatistical Breviaryof18 1.

Thepiechart isperhaps themost ubiquitousstatistical chart in thebusinessworld

and themassmedia. It canalsohelppeopledowork. However, it hasbeencritici ed,and

somerecommendavoiding it,pointingout inparticular that it isdifficult tocomparedifferent

sectionsofagivenpiechart,or tocomparedataacrossdifferent piecharts. Piechartscan

beaneffectivewayofdisplaying information insomecases, inparticular if the intent is to

compare the si eof a slicewith thewhole pie, rather than comparing the slicesamong

them. Piechartsworkparticularlywell when theslicesrepresent 5 to 5 % of thedata,but

ingeneral,otherplotssuchas thebarchart or thedot plot,ornon-graphical methodssuch

as tables,maybemoreadapted forrepresentingcertain information.

DIAGRAM 1.2 : EXAMPLE OF PIE CHART

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CONCLUSION

Statistics is the science of making effective use of numerical data relating to groups

of individuals or experiments. It deals with all aspects of this, including not only the

collection, analysis and interpretation of such data, but also the planning of the collection of

data, in terms of the design of surveys and experiments. In this assignment, the data

collection is about the siblings among 0 students out of whole students of one of the

college.

rom this data collected, there is represented using bar graph, histogram,

frequency polygon and pie chart. he data was represented using these graphs to make it

easier to read by the statistician. Statistician will get many data when the data is

representing using visual representative. ne of them is mode. Mode is the higher number

of the data. When the data is representing using bar graph or histogram , it is very clear and

easier to know the mode. ust take the higher one. ther than that, visual representative

also can help statistician easy to find mean and median.

In the other hand, by using data representative we can get a lot of information from

the data. We will get the highest, the higher, the lower a nd the lowest number of the data

that we are collect. rom the graph also we will get doubled or triple data rather than just

using tabled representation or raw data. he information we are collected from the visual

representative are stayed at the page in front in analysis.

Last but not least, we want to highlight that visual representative is very important in

statistics. his is because a list of raw data may be difficult to interpret; psychologists prefer

to represent their data in an organized way. wo of the most common ways are frequency

distributions and graphs. here are many types of visual representative of data in statistics

such as histogram, bar chart, pie chart, line graph, frequency polygon and others. So,choose what is suitable for your data and make it easier.

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Basic Math 2010