An introduction to statistics +1 (7.5.15)

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AN INTRODUCTION TO

STATISTICS

sWiKAkI -ie`k jwx pihcwx

pySkS; bldyv isMG , lYkcrwr ieknwimks, s.s.s.s.huiSAwrpur(s.A.s.ngr) 84270-04513

1

HISTORY OF STATISTICS

‘STATISTICS’ lwqInI BwSw dy Sbd “STATUS”

jW ietwlIAn Sbd “STATISTA” mqlb‘POLITICAL STATE’

sWiKAkI, purwqn SwSkW duAwrw Awpxy rwj dIPOjI SkqI ,Dn-dOlq, krW Aqy hor m`uidAW bwryjwxkwrI leI rwj dI BUmI, KyqIbwVI, vpwr,jnsMiKAw bwry AMkVy ley jWdy[9vIN sdI iv`c iesmwimk gixq SwsqrIAL-KINDI ny sB qoN pihlW ‘STATISTICS’

Sbd dI vrqoN kIqI[2

sWiKAkI kI hY?sWiKAkI sMiKAwqmk sUcnwvW dw BMfwr[sWiKAkI, Bwv kuJ nqIijAWnMU igAwq krn leIsMiKAwqmk sUcnwvW ArQwqAMkiVAW nMU ie`kTw krnw,vrgIkrn, ivSlySx qyinrvcn nwl sMbMDq qknIkWAqy aupwvW qoN hY[

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sWiKAkI ivsiqRq Awkwr kwrn do rUpW iv`c pirBwiSq

ie`k vcn Singular

bhuvcn Plural

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bhuvcn (Plural) sWiKAkI AMkW dy rUp iv`c drsweIsUcnw, e.g. jnsMiKAw sbMDIAMkVy, ruzgwr, srvjnkKrc [koeI ie`k sMiKAwqmk q`qsWiKAkI nhIN, e.g. sunIl nMU1500 ru; pRqI mhInw jybKrc imldw hY[sWiKAkI AMkiVAW dy smUhjW AOsq nMU ikhw jWdw,e.g.

igAwrvI jmwq dy ivid;dwAOsq jyb Krc 1500 ru:[

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bhuvcn (Plural) dy rUp iv`c sWiKAkI dI pirBwSw

“bhuvcn dy rUp iv`c sWiKAkI qoN Bwv sMiKAwqimk AMkiVAW qoN hY[sWiKAkI gxnw dw ivigAwn hY.” A. L. Bowley

“sWiKAkI q`QW dy pirmwxwqimk pihlUAW dy sMiKAwqimk ivvrx hn jo mdW dI igxqI jW mwp dy rUp iv`c pRgt krdy hn ”

–Wallis and Roberts

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sWiKAkI dI bhuvcn sMiKAw smMkW dy rUp iv`c ivSySqwvW

• 1.q`QW dw smUh (Aggregate of Facts)• 2.sMiKAwvW iv`c pyS krnw

(Numerically Expressed)• 3.AnykW krnW qoN pRBwivq

(Affected by Multiplicity of Causes)

Characteristics of Statistics in Terms of Numerical Data or

in Plural Sense.

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sWiKAkI dI bhuvcn sMiKAw smMkW dy rUp iv`c ivSySqwvW

• 4.au`icq mwqrw iv`c Su`Dqw (Reasonable Accuracy)

• 5.ie`k-dUjy nwl sbMiDq rUp iv`c hoxw (Placed in Relation to each other)

• 6.pUrv-inSicq audyS (pre-determined Purpose)

Characteristics of Statistics in Terms of Numerical

Data or in Plural Sense.

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sWiKAkI dI bhuvcn sMiKAw smMkW dy rUp iv`c ivSySqwvW

• 7.gxnw Aqy Anumwn (Enumerated or Estimated)

• 8.ivDIb`D FMg nwl iek`Tw krnw (Collection in Systematic Manner)

Characteristics of Statistics in Terms of Numerical

Data or in Plural Sense.

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ie`k vcn (Singular) sWiKAkI

ie`k vcn sWiKAkI dw ArQ sWiKAkI ivDIAW (Statistical Methods) qoN hY[jo sMiKAwqimk AMkiVAWdy sMkln krn, vrgIkrx,pySIkrx, ivSlySx Aqyinrvcn dw AiDAYn krdIhY[

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ie`k vcn (Singular) dy rUp iv`c sWiKAkI dI pirBwSw

“sWiKAkI nMU sMiKAwqimk AMkiVAW dwsMgRihkrn, pRdrSn, ivSlySx Aqysp`StIkrx nwl sMbMiDq ivigAwn ikhw jwskdw hY[” kwrks`tn Aqy kwaUfyn

“sWiKAkI auh ivigAwn hY jo iksy ivSy qypRkwS pwaux dy audyS nwl sMgRih kIqy geyAMkiVAW dy sMgRihx ,vrgIkrx, pRdrSn,qulnw Aqy ivAwiKAw krn dIAW ivDIAW dIivvycnw krdw hY[ ” - sYlgmYn

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sWiKAkI AiDAYn dIAW AvsQwvW

• Stages of Statistical Study.

AMkiVAW dw sMkln

AMkiVAW dw ivvsQIkrx

AMkiVAW dw pySIkrx

AMkiVAW dw ivSlySx

AMkiVAW dw inrvcn12

sWiKAkI aupkrx (Statistical Tools)

Stage I AMkiVAW dw sMgRih (Collection of Data)

sMgxnw (Census) nmUnw (Sampling)

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sWiKAkI aupkrx (Statistical Tools)

Stage II AMkiVAW dw ivvsQIkrx (Organisation

of Data)

AMkiVAW dI qrqIb imlwn ryKw(Tally Bar)

(Array of Data)

Element 1

Element 2

Element 3

Element 4

Element 514

sWiKAkI aupkrx (Statistical Tools)

Stage III AMkiVAW dw pySIkrx (Presentation of

Data)

qwilkw (Table) grw&(Graph) ic`qr (Diagrames)

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sWiKAkI aupkrx (Statistical Tools)

Stage IV AMkiVAW dw ivSlySx(Analysis of Data)

AOsq (Average) pRqISq(Percentage)

sihsbMD (Correlation)

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mzdUr kulauqpwdn

Aosqauqpwdn

1 20 202 50 253 90 304 160 405 250 506 240 40

sWiKAkI aupkrx (Statistical Tools)

Stage V AMkiVAW dw inrvcn(Interpretation of Data)

AOsq ,pRqISq dw ivsQwr Aqy iviBMn AwriQk crW nwl sMbMD dI ifgrI

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sWiKAkI dI pRikRqI(Nature Of Statistics)

ivigAwn qy klw donoN[AMkiVAW dw ivDIb`D AiDAYn[klw; vwsqivk jIvn dIAWsm`isAwvW sulJwaux leIAMkiVAW dw pRXog[kuJ ivdvwnW : ivigAwn nhINsWiKAkI ivDIAW dwAiDAYn[ivDIAW dw swryivigAwnW iv`c pRXog[

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sWiKAkI dI ivSw sm`grI(Subject Matter Of Statistics)

sWiKAkI dI ivSw sm`grI

ivvrxb`D (Descriptive)

is`twb`D (Inferential)

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ivvrxb`D sWiKAkI (Descriptive Statistics)

ivDIAW jo AMkiVAW nMU iek`Tw krn , qwilkwvW,ryKwic`qrW Awid rwhIN pyS krn ,ivSySqwvW dyivvrx pyS krn leI pRXog kIqIAW jWdIAW[

AOsq, miDAkw, ivcln dy mwp Swiml[

igAwrvIN jmwq dy 100 ivid: dy AOsq AMk pqwkrdy hW[

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is`twb`D sWiKAkI (Inferential Statistics)

ivDIAW ijMnHW rwhIN iksy sYNpl(Sample)dy AwDwr qy sm`gr(Population) dy sbMD iv`c

is`ty k`Fy jWdy hn[

jykr AiDAwpk sYNpl AMkW(Sample Marks)dy AwDwr qyswry ividAwrQIAW dy AMklgwaux dw PYslw krdw hY qWauh is`tyb`D sWiKAkI dw pRXogkr irhw hY

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sWiKAkI AiDAYn dIAW swrIAW mdW jW iekweIAW dw smUh; jy 1000

ivid:dw AiDAYn qW jnsMiKAw dw Awkwr 1000.

sWiKAkI dIAW sImwvW ( Limitations of Statistics)

isrP sMiKAwqimk q`QW dw AiDAYn[isrP smUhW dw AiDAYn[AMkiVAW iv`c ie`k rUpqw jW ie`kswrqw dw

hoxw[ pirxwm isrP AOsqn s`c huMdy hn[ibnW sMdrB is`ty glq ho skdy hn[isrP mwihrW rwhIN pRXog[durpRXog sMBv[

22

ArQSwsqr iv`c sWiKAkI dw mh`qv( Importance of Statistics In Economics)

• AwriQk sm`isAwvW dI pirmwxwqimk ivAwiKAw• AMqr-KyqrI Aqy AMqr-smW qulnwvW

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ArQSwsqr iv`c sWiKAkI dw mh`qv( Importance of Statistics In Economics)

• kwrn pirxwm sMbMD pqw krnw• AwriQk isDWqW dw inrmwx

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ArQSwsqr iv`c sWiKAkI dw mh`qv( Importance of Statistics In Economics)

• AwriQk Biv`KbwxI• nIqIAW dw inrmwx• AwriQk sMquln

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Objective Type Question• pR:1.hyT iliKAW iv`coN ikhVw kQn sWiKAkI

nhIN hY?• (a) Bwrq iv`c AOsq jnm dr 35 pRqI hzwr hY jd

ik AmrIkw iv`c 13 pRqI hzwr hY[ • (b) rvnIq dI jyb iv`c 1000 ru: dw not hY[• (c) iqaUV skUl dI tIm ny 3 mYc ij`qy hn Aqy 2

hwry hn[ • (d) igAwrvIN jmwq dy hryk ividAwrQI dw AOsq

jyb Krc 500 ru: pRqI mhInw hY[• auq`r: (b) rvnIq dI jyb iv`c 1000 ru: dw not

hY[

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Objective Type Question

• pR:2. sWiKAkI dy sbMD iv`c ikhVw shI hYY?• (a) q`QW dw smUh• (b) sMiKAwvW iv`c drswauxw• (c) bhuq swry q`qW qoN pRBwivq • (d) aupr ilKy swry

• auq`r: (d) aupr ilKy swry[

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Objective Type Question

• pR:3. hyTW ilKy iv`coN ikhVw sWiKAkI dw ivSw nhIN hYY?

• (a) kyNdrI pRivrqI dw mwp• (b) ivcln dw mwp• (c) sUck AMk igAwq krnw• (d) ienHW iv`coN koeI vI nhIN

• auq`r: (c) sUck AMk igAwq krnw[

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Objective Type Question

• pR:4. sWiKAkI AiDAYn dIAW ikMnIAW AvsQwvW hn ?

(a) do(b) cwr( c) pMj(d) s`q

• auq`r: (c) pMj [

29

Objective Type Question

KwlI QW iv`c shI Sbd cux ky Bro[pR:5. sWiKAkI ………… qoN pRBwivq huMdI hY[

(ie`k kwrn , bhuq swry kwrnW qoN)auq`r:- bhuq swry kwrnW qoN[

pR:6. swry AMkVy sWiKAkI …………[(huMdy hn , nhIN huMdy hn)

auq`r :- nhIN huMdy hn30

Objective Type QuestionKwlI QW iv`c shI Sbd cux ky Bro[

pR:7. bhuvcn dy rUp iv`c sWiKAkI dw ArQ …… qoN hY[

(AMkiVAW , sWiKAkI ivDIAW)auq`r:- AMkiVAW[

pR:8.ie`kvcn dy rUp iv`c sWiKAkI dw ArQ ………qoN hY[

(AMkiVAW , sWiKAkI ivDIAW)auq`r :- sWiKAkI ivDIAW[

31

Objective Type Question

shI / glq d`sopR:9. sWiKAkI iv`c guxwqmk crW dw AiDAYn

kIqw jWdw hY[ (shI , glq)auq`r:- glq[

pR:10. sWiKAkI iv`c mwqrwqmk crW dw AiDAYn kIqw jWdw hY[ shI , glq)

auq`r :- glq[

32

pySkS:bldyv isMG, lYkcrwr ArQSwsqr

s.s.s.s.huiSAwrpur(swihbzwdw AjIq isMG ngr)

mob:84270-0451333

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