An introduction to statistics +1 (7.5.15)
- 1. 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
- 2. HISTORY OF STATISTICS ‘STATISTICS’ lwqInI BwSw dy Sbd “STATUS” jW ietwlIAn Sbd “STATISTA” mqlb ‘POLITICAL STATE’ sWiKAkI, purwqn SwSkW duAwrw Awpxy rwj dI POjI SkqI ,Dn-dOlq, krW Aqy hor m`uidAW bwry jwxkwrI leI rwj dI BUmI, KyqIbwVI, vpwr, jnsMiKAw bwry AMkVy ley jWdy[ 9vIN sdI iv`c iesmwimk gixq SwsqrI AL-KINDI ny sB qoN pihlW ‘STATISTICS’ Sbd dI vrqoN kIqI[ 2
- 3. sWiKAkI kI hY? sWiKAkI sMiKAwqmk sUcnwvW dw BMfwr[ sWiKAkI, Bwv kuJ nqIijAW nMU igAwq krn leI sMiKAwqmk sUcnwvW ArQwq AMkiVAW nMU ie`kTw krnw, vrgIkrn, ivSlySx qy inrvcn nwl sMbMDq qknIkW Aqy aupwvW qoN hY[ 3
- 4. sWiKAkI ivsiqRq Awkwr kwrn do rUpW iv`c pirBwiSq ie`k vcn Singular bhuvcn Plural 4
- 5. bhuvcn (Plural) sWiKAkI AMkW dy rUp iv`c drsweI sUcnw, e.g. jnsMiKAw sbMDI AMkVy, ruzgwr, srvjnk Krc [ koeI ie`k sMiKAwqmk q`q sWiKAkI nhIN, e.g. sunIl nMU 1500 ru; pRqI mhInw jyb Krc imldw hY[ sWiKAkI AMkiVAW dy smUh jW AOsq nMU ikhw jWdw,e.g. igAwrvI jmwq dy ivid;dw AOsq jyb Krc 1500 ru:[ 5
- 6. 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 6
- 7. 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. 7
- 8. 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. 8
- 9. 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. 9
- 10. ie`k vcn (Singular) sWiKAkI ie`k vcn sWiKAkI dw ArQ sWiKAkI ivDIAW (Statistical Methods) qoN hY[ jo sMiKAwqimk AMkiVAW dy sMkln krn, vrgIkrx, pySIkrx, ivSlySx Aqy inrvcn dw AiDAYn krdI hY[ 10
- 11. ie`k vcn (Singular) dy rUp iv`c sWiKAkI dI pirBwSw “sWiKAkI nMU sMiKAwqimk AMkiVAW dw sMgRihkrn, pRdrSn, ivSlySx Aqy sp`StIkrx nwl sMbMiDq ivigAwn ikhw jw skdw hY[” kwrks`tn Aqy kwaUfyn “sWiKAkI auh ivigAwn hY jo iksy ivSy qy pRkwS pwaux dy audyS nwl sMgRih kIqy gey AMkiVAW dy sMgRihx ,vrgIkrx, pRdrSn, qulnw Aqy ivAwiKAw krn dIAW ivDIAW dI ivvycnw krdw hY[ ” - sYlgmYn 11
- 12. sWiKAkI AiDAYn dIAW AvsQwvW • Stages of Statistical Study. AMkiVAW dw sMkln AMkiVAW dw ivvsQIkrx AMkiVAW dw pySIkrx AMkiVAW dw ivSlySx AMkiVAW dw inrvcn 12
- 13. sWiKAkI aupkrx (Statistical Tools) Stage I AMkiVAW dw sMgRih (Collection of Data) sMgxnw (Census) nmUnw (Sampling) 13
- 14. 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 5 14
- 15. sWiKAkI aupkrx (Statistical Tools) Stage III AMkiVAW dw pySIkrx (Presentation of Data) qwilkw (Table) grw&(Graph) ic`qr (Diagrames) 15
- 16. sWiKAkI aupkrx (Statistical Tools) Stage IV AMkiVAW dw ivSlySx(Analysis of Data) AOsq (Average) pRqISq(Percentage) sihsbMD (Correlation) 16 mzdUr ku`l auqpwdn Aosq auqpwdn 1 20 20 2 50 25 3 90 30 4 160 40 5 250 50 6 240 40
- 17. sWiKAkI aupkrx (Statistical Tools) Stage V AMkiVAW dw inrvcn (Interpretation of Data) AOsq ,pRqISq dw ivsQwr Aqy iviBMn AwriQk crW nwl sMbMD dI ifgrI 17
- 18. sWiKAkI dI pRikRqI (Nature Of Statistics) ivigAwn qy klw donoN[ AMkiVAW dw ivDIb`D AiDAYn[ klw; vwsqivk jIvn dIAW sm`isAwvW sulJwaux leI AMkiVAW dw pRXog[ kuJ ivdvwnW : ivigAwn nhIN sWiKAkI ivDIAW dw AiDAYn[ivDIAW dw swry ivigAwnW iv`c pRXog[ 18
- 19. sWiKAkI dI ivSw sm`grI (Subject Matter Of Statistics) sWiKAkI dI ivSw sm`grI ivvrxb`D (Descriptive) is`twb`D (Inferential) 19
- 20. ivvrxb`D sWiKAkI (Descriptive Statistics) ivDIAW jo AMkiVAW nMU iek`Tw krn , qwilkwvW ,ryKwic`qrW Awid rwhIN pyS krn ,ivSySqwvW dy ivvrx pyS krn leI pRXog kIqIAW jWdIAW[ AOsq, miDAkw, ivcln dy mwp Swiml[ igAwrvIN jmwq dy 100 ivid: dy AOsq AMk pqw krdy hW[ 20
- 21. 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 qy swry ividAwrQIAW dy AMk lgwaux dw PYslw krdw hY qW auh is`tyb`D sWiKAkI dw pRXog kr irhw hY 21 sWiKAkI AiDAYn dIAW swrIAW mdW jW iekweIAW dw smUh; jy 1000 ivid:dw AiDAYn qW jnsMiKAw dw Awkwr 1000.
- 22. 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
- 23. ArQSwsqr iv`c sWiKAkI dw mh`qv ( Importance of Statistics In Economics) • AwriQk sm`isAwvW dI pirmwxwqimk ivAwiKAw • AMqr-KyqrI Aqy AMqr-smW qulnwvW 23
- 24. ArQSwsqr iv`c sWiKAkI dw mh`qv ( Importance of Statistics In Economics) • kwrn pirxwm sMbMD pqw krnw • AwriQk isDWqW dw inrmwx 24
- 25. ArQSwsqr iv`c sWiKAkI dw mh`qv ( Importance of Statistics In Economics) • AwriQk Biv`KbwxI • nIqIAW dw inrmwx • AwriQk sMquln 25
- 26. 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[ 26
- 27. 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[ 27
- 28. 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[ 28
- 29. 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
- 30. 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 hn 30
- 31. Objective Type Question KwlI 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
- 32. Objective Type Question shI / glq d`so pR: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
- 33. pySkS: bldyv isMG, lYkcrwr ArQSwsqr s.s.s.s.huiSAwrpur (swihbzwdw AjIq isMG ngr) mob:84270-04513 33