PPT on An Introduction to Statistics In Punjabi Medium

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