SlideShare a Scribd company logo
1 of 23
MATHEMATICAL STATISTICS - I
Prepared by
Ms. R. Umadevi
Assistant Professor
Department of Mathematics
Bon Secours College For Women
Thanjavur
MEASURES OF DISPERSION
Definition
Dispersion is a measure of variation of the items
Properties
(i) It should be capable of treating it by Algebraic or Statistical techniques
(ii) It should be easy to calculate
(iii) It should be easy to understand
(iv) It must not be affected by different samples or fluctuation of sampling
Types of Measures
(i) Absolute Measures
(ii) Relative Measures
Absolute Measure
Absolute measures of dispersion are expressed in same units in
which original data is presented but these measures cannot be used to
compare the variations between the two series.
Relative Measure
Relative measures are not expressed in units but it is a pure number.
It is the ration of absolute dispersion to an appropriate average such as
coefficient of standard deviation or coefficient of mean deviation.
Methods of Measuring Dispersion
(i) Range and Coefficient of Range
(ii) Quartile Deviation and Coefficient of Quartile Deviation
(iii) Mean Deviation and Coefficient of Mean Deviation
(iv) Standard Deviation and Coefficient of Standard Deviation
Range
It is the simplest of the values of Dispersion. It is merely
the difference between the largest and smallest term.
Range = L – S
Coefficient of Range =
It is also known as Ratio of range or coefficient of
Scatteredness.
S
L
S
L


Merits or Uses
(i) It is easiest to calculate and simplest to understand.
(ii) It is one of those measures which are rigidly defined.
(iii) It gives us the total picture of the problem even with a single glance.
(iv) It is used to check the quality of a product for quality control. Range
plays an important role in preparing R – charts, thus quality is
maintained.
(v) The idea about the price of Gold and Shares is also made
taking care of the range in which prices have moved for the past
some periods.
(vi) Meteorological department also makes forecasts about the
weather by keeping range of temperature in view.
Demerits or Limitations
(i) Range is not based on all the terms.
(ii) Due to above reason range is not a reliable measure of
dispersion.
(iii) Range does not change even the least even if all other, in
between, terms and variables are changed.
(iv) Range is too much affected by fluctuation of sampling.
(v) It does not tell us anything about the variability of
other data.
(vi) For open – end intervals, range is indeterminate.
Quartile Deviation
This measure gives a little more knowledge about the
distribution which the range does not give.
Inter Quartile Range = Q3 – Q1
Quartile Deviation =
Q1 = Size of
Q3 = Size of
2
1
3 Q
Q 
term
N
th





 
4
1
term
N
th





 
4
)
1
(
3
Merits or Uses
(i) It can be easily calculated and simply understood.
(ii) It does not involve much mathematical difficulties.
(iii) As it takes middle 50% terms hence it is a measure better than range.
(iv) It is not affected by extreme terms as 25% of upper and 25% of
lower terms are left out.
Demerits or Limitations
(i) As Q1 and Q3 are both positional measures hence are not
capable of further algebraic treatment.
(ii) Calculation are much more, but the result obtained is not of
much importance.
(iii) It is too much affected by fluctuations of sample.
(iv) 50% terms play no role, first and last 25% items ignored may
not give reliable result.
(v) If the values are irregular, then result is affected badly.
Mean Deviation
Mean Deviation of a set of observations of a series is the
arithmetic mean of all the deviations, without their algebraic
signs, taken from its central value.
Mean Deviation =
Coefficient of Mean Deviation =
N
D
f

x
n
o
i
t
a
i
v
e
D
n
a
e
M
Merits or Uses
(i) As in case of , every term is taken in account. Hence it is
certainly a better measure than other measures of dispersion.
(ii) Mean deviation is extensively used in other fields such as
Economics, Business, Commerce or any other field of such type.
x
(iii) It has least sampling fluctuations as compared to Range,
Percentile and Quartile Deviation.
(iv) When Comparison is needed this is perhaps the best
measure.
(v) Mean Deviation is rigidly defined.
Standard Deviation
It is defined as the square root of the mean of the squared
deviation from the actual mean. It is also called the root mean
square deviation.
S.D. =
Coefficient of S.D. =
N
x
x
  2
)
(
x

Variance
It is the square of standard deviation.
Variance = σ 2
Coefficient of Variance
It is used to find the relative change that is said to exist in
two or more series.
C.V = 100

x

Merits or Uses
(i) This is the most rigidly defined measure of dispersion and
therefore is dependable.
(ii) It is further capable of algebraic treatment.
(iii) It is based on all the terms or observations hence is more
reliable.
Demerits or Limitations
(i) As compared with other measures of dispersion it is more
difficult to compute and not so easy to understand.
(ii) In the case of open end intervals we have to make the
assumption of lower limit of first interval and upper limit of last
interval
(iii) As far as S.D. is concerned it does not compare two series itself. We
have to proceed to coefficient of S.D. or C.V. for this purpose.
(iv) The extreme terms make the impact two much, therefore in some
cases coefficient of Q.D. or of M.D. has a certain edge over it. If extreme
item differ largely, then they make a heavy change when deviations are
squared.
Mathematical Statistics I.pptx

More Related Content

Similar to Mathematical Statistics I.pptx

6.describing a distribution
6.describing a distribution6.describing a distribution
6.describing a distributionSonu Kumar
 
Measures of dispersion
Measures of dispersionMeasures of dispersion
Measures of dispersionDrZahid Khan
 
Final statistical treatment data
Final statistical treatment dataFinal statistical treatment data
Final statistical treatment dataJLoknathDora
 
Measures of Dispersion
Measures of DispersionMeasures of Dispersion
Measures of DispersionMohit Mahajan
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptaigil2
 
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happiness
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_HappinessUnit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happiness
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happinessourbusiness0014
 
Mba i qt unit-2.1_measures of variations
Mba i qt unit-2.1_measures of variationsMba i qt unit-2.1_measures of variations
Mba i qt unit-2.1_measures of variationsRai University
 
Measures of dispersion or variation
Measures of dispersion or variationMeasures of dispersion or variation
Measures of dispersion or variationRaj Teotia
 
State presentation2
State presentation2State presentation2
State presentation2Lata Bhatta
 
Found_651466665_1124864.ppt
Found_651466665_1124864.pptFound_651466665_1124864.ppt
Found_651466665_1124864.pptSunil kumar
 
measure of variability (windri). In research include example
measure of variability (windri). In research include examplemeasure of variability (windri). In research include example
measure of variability (windri). In research include examplewindri3
 
Multicolinearity
MulticolinearityMulticolinearity
MulticolinearityPawan Kawan
 
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )Neeraj Bhandari
 
Lecture. Introduction to Statistics (Measures of Dispersion).pptx
Lecture. Introduction to Statistics (Measures of Dispersion).pptxLecture. Introduction to Statistics (Measures of Dispersion).pptx
Lecture. Introduction to Statistics (Measures of Dispersion).pptxNabeelAli89
 
Measures of Dispersion.pptx
Measures of Dispersion.pptxMeasures of Dispersion.pptx
Measures of Dispersion.pptxVanmala Buchke
 
Measure of dispersion
Measure of dispersionMeasure of dispersion
Measure of dispersionWaqar Abbasi
 
Topic 4 Measures of Dispersion & Numericals.pptx
Topic 4  Measures of Dispersion & Numericals.pptxTopic 4  Measures of Dispersion & Numericals.pptx
Topic 4 Measures of Dispersion & Numericals.pptxCallplanetsDeveloper
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyPrithwis Mukerjee
 

Similar to Mathematical Statistics I.pptx (20)

Statistics report THE RANGE
Statistics report THE RANGEStatistics report THE RANGE
Statistics report THE RANGE
 
6.describing a distribution
6.describing a distribution6.describing a distribution
6.describing a distribution
 
Measures of dispersion
Measures of dispersionMeasures of dispersion
Measures of dispersion
 
Final statistical treatment data
Final statistical treatment dataFinal statistical treatment data
Final statistical treatment data
 
Measures of Dispersion
Measures of DispersionMeasures of Dispersion
Measures of Dispersion
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .ppt
 
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happiness
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_HappinessUnit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happiness
Unit 5 8614.pptx A_Movie_Review_Pursuit_Of_Happiness
 
Mba i qt unit-2.1_measures of variations
Mba i qt unit-2.1_measures of variationsMba i qt unit-2.1_measures of variations
Mba i qt unit-2.1_measures of variations
 
Measures of dispersion or variation
Measures of dispersion or variationMeasures of dispersion or variation
Measures of dispersion or variation
 
State presentation2
State presentation2State presentation2
State presentation2
 
Found_651466665_1124864.ppt
Found_651466665_1124864.pptFound_651466665_1124864.ppt
Found_651466665_1124864.ppt
 
measure of variability (windri). In research include example
measure of variability (windri). In research include examplemeasure of variability (windri). In research include example
measure of variability (windri). In research include example
 
Multicolinearity
MulticolinearityMulticolinearity
Multicolinearity
 
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )
Measure of dispersion by Neeraj Bhandari ( Surkhet.Nepal )
 
Lecture. Introduction to Statistics (Measures of Dispersion).pptx
Lecture. Introduction to Statistics (Measures of Dispersion).pptxLecture. Introduction to Statistics (Measures of Dispersion).pptx
Lecture. Introduction to Statistics (Measures of Dispersion).pptx
 
Measures of Dispersion.pptx
Measures of Dispersion.pptxMeasures of Dispersion.pptx
Measures of Dispersion.pptx
 
Measure of dispersion
Measure of dispersionMeasure of dispersion
Measure of dispersion
 
Measures of dispersion
Measures  of  dispersionMeasures  of  dispersion
Measures of dispersion
 
Topic 4 Measures of Dispersion & Numericals.pptx
Topic 4  Measures of Dispersion & Numericals.pptxTopic 4  Measures of Dispersion & Numericals.pptx
Topic 4 Measures of Dispersion & Numericals.pptx
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central Tendency
 

More from umadeviR3

Bridge Course.pptx
Bridge Course.pptxBridge Course.pptx
Bridge Course.pptxumadeviR3
 
Refraction.pptx
Refraction.pptxRefraction.pptx
Refraction.pptxumadeviR3
 
Astronomy.pptx
Astronomy.pptxAstronomy.pptx
Astronomy.pptxumadeviR3
 
Real Analysis - quiz
Real Analysis - quizReal Analysis - quiz
Real Analysis - quizumadeviR3
 
Celestial coordinates
Celestial coordinatesCelestial coordinates
Celestial coordinatesumadeviR3
 
Real life application
Real life applicationReal life application
Real life applicationumadeviR3
 
Operation Research
Operation ResearchOperation Research
Operation ResearchumadeviR3
 
Projectile motion
Projectile motionProjectile motion
Projectile motionumadeviR3
 

More from umadeviR3 (19)

Bridge Course.pptx
Bridge Course.pptxBridge Course.pptx
Bridge Course.pptx
 
Refraction.pptx
Refraction.pptxRefraction.pptx
Refraction.pptx
 
Astronomy.pptx
Astronomy.pptxAstronomy.pptx
Astronomy.pptx
 
Real Analysis - quiz
Real Analysis - quizReal Analysis - quiz
Real Analysis - quiz
 
Stat.pptx
Stat.pptxStat.pptx
Stat.pptx
 
Ode unit 5
Ode unit 5Ode unit 5
Ode unit 5
 
Ode unit 4
Ode unit 4Ode unit 4
Ode unit 4
 
Ode unit 4
Ode unit 4Ode unit 4
Ode unit 4
 
Ode unit 3
Ode unit 3Ode unit 3
Ode unit 3
 
Ode unit 2
Ode unit 2Ode unit 2
Ode unit 2
 
Ode unit 1
Ode unit 1Ode unit 1
Ode unit 1
 
Celestial coordinates
Celestial coordinatesCelestial coordinates
Celestial coordinates
 
Real life application
Real life applicationReal life application
Real life application
 
Numerical
NumericalNumerical
Numerical
 
Operation Research
Operation ResearchOperation Research
Operation Research
 
Numerical
NumericalNumerical
Numerical
 
Season
SeasonSeason
Season
 
Friction
FrictionFriction
Friction
 
Projectile motion
Projectile motionProjectile motion
Projectile motion
 

Recently uploaded

Animal Communication- Auditory and Visual.pptx
Animal Communication- Auditory and Visual.pptxAnimal Communication- Auditory and Visual.pptx
Animal Communication- Auditory and Visual.pptxUmerFayaz5
 
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...chandars293
 
Biopesticide (2).pptx .This slides helps to know the different types of biop...
Biopesticide (2).pptx  .This slides helps to know the different types of biop...Biopesticide (2).pptx  .This slides helps to know the different types of biop...
Biopesticide (2).pptx .This slides helps to know the different types of biop...RohitNehra6
 
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdfPests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdfPirithiRaju
 
GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)Areesha Ahmad
 
Botany 4th semester series (krishna).pdf
Botany 4th semester series (krishna).pdfBotany 4th semester series (krishna).pdf
Botany 4th semester series (krishna).pdfSumit Kumar yadav
 
Seismic Method Estimate velocity from seismic data.pptx
Seismic Method Estimate velocity from seismic  data.pptxSeismic Method Estimate velocity from seismic  data.pptx
Seismic Method Estimate velocity from seismic data.pptxAlMamun560346
 
Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )aarthirajkumar25
 
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLKochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLkantirani197
 
Presentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxPresentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxgindu3009
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)Areesha Ahmad
 
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxCOST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxFarihaAbdulRasheed
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPirithiRaju
 
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptxSCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptxRizalinePalanog2
 
Bacterial Identification and Classifications
Bacterial Identification and ClassificationsBacterial Identification and Classifications
Bacterial Identification and ClassificationsAreesha Ahmad
 
Isotopic evidence of long-lived volcanism on Io
Isotopic evidence of long-lived volcanism on IoIsotopic evidence of long-lived volcanism on Io
Isotopic evidence of long-lived volcanism on IoSérgio Sacani
 
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceuticsPulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceuticssakshisoni2385
 
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 60009654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000Sapana Sha
 
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...Sérgio Sacani
 

Recently uploaded (20)

Animal Communication- Auditory and Visual.pptx
Animal Communication- Auditory and Visual.pptxAnimal Communication- Auditory and Visual.pptx
Animal Communication- Auditory and Visual.pptx
 
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...
High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...
 
Biopesticide (2).pptx .This slides helps to know the different types of biop...
Biopesticide (2).pptx  .This slides helps to know the different types of biop...Biopesticide (2).pptx  .This slides helps to know the different types of biop...
Biopesticide (2).pptx .This slides helps to know the different types of biop...
 
CELL -Structural and Functional unit of life.pdf
CELL -Structural and Functional unit of life.pdfCELL -Structural and Functional unit of life.pdf
CELL -Structural and Functional unit of life.pdf
 
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdfPests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf
Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf
 
GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)
 
Botany 4th semester series (krishna).pdf
Botany 4th semester series (krishna).pdfBotany 4th semester series (krishna).pdf
Botany 4th semester series (krishna).pdf
 
Seismic Method Estimate velocity from seismic data.pptx
Seismic Method Estimate velocity from seismic  data.pptxSeismic Method Estimate velocity from seismic  data.pptx
Seismic Method Estimate velocity from seismic data.pptx
 
Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )
 
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLKochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
 
Presentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxPresentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptx
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)
 
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxCOST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
 
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptxSCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx
 
Bacterial Identification and Classifications
Bacterial Identification and ClassificationsBacterial Identification and Classifications
Bacterial Identification and Classifications
 
Isotopic evidence of long-lived volcanism on Io
Isotopic evidence of long-lived volcanism on IoIsotopic evidence of long-lived volcanism on Io
Isotopic evidence of long-lived volcanism on Io
 
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceuticsPulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
 
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 60009654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
 
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
 

Mathematical Statistics I.pptx

  • 1. MATHEMATICAL STATISTICS - I Prepared by Ms. R. Umadevi Assistant Professor Department of Mathematics Bon Secours College For Women Thanjavur
  • 3. Definition Dispersion is a measure of variation of the items Properties (i) It should be capable of treating it by Algebraic or Statistical techniques (ii) It should be easy to calculate (iii) It should be easy to understand (iv) It must not be affected by different samples or fluctuation of sampling Types of Measures (i) Absolute Measures (ii) Relative Measures
  • 4. Absolute Measure Absolute measures of dispersion are expressed in same units in which original data is presented but these measures cannot be used to compare the variations between the two series. Relative Measure Relative measures are not expressed in units but it is a pure number. It is the ration of absolute dispersion to an appropriate average such as coefficient of standard deviation or coefficient of mean deviation.
  • 5. Methods of Measuring Dispersion (i) Range and Coefficient of Range (ii) Quartile Deviation and Coefficient of Quartile Deviation (iii) Mean Deviation and Coefficient of Mean Deviation (iv) Standard Deviation and Coefficient of Standard Deviation
  • 6. Range It is the simplest of the values of Dispersion. It is merely the difference between the largest and smallest term. Range = L – S Coefficient of Range = It is also known as Ratio of range or coefficient of Scatteredness. S L S L  
  • 7. Merits or Uses (i) It is easiest to calculate and simplest to understand. (ii) It is one of those measures which are rigidly defined. (iii) It gives us the total picture of the problem even with a single glance. (iv) It is used to check the quality of a product for quality control. Range plays an important role in preparing R – charts, thus quality is maintained.
  • 8. (v) The idea about the price of Gold and Shares is also made taking care of the range in which prices have moved for the past some periods. (vi) Meteorological department also makes forecasts about the weather by keeping range of temperature in view.
  • 9. Demerits or Limitations (i) Range is not based on all the terms. (ii) Due to above reason range is not a reliable measure of dispersion. (iii) Range does not change even the least even if all other, in between, terms and variables are changed.
  • 10. (iv) Range is too much affected by fluctuation of sampling. (v) It does not tell us anything about the variability of other data. (vi) For open – end intervals, range is indeterminate.
  • 11. Quartile Deviation This measure gives a little more knowledge about the distribution which the range does not give. Inter Quartile Range = Q3 – Q1 Quartile Deviation = Q1 = Size of Q3 = Size of 2 1 3 Q Q  term N th        4 1 term N th        4 ) 1 ( 3
  • 12. Merits or Uses (i) It can be easily calculated and simply understood. (ii) It does not involve much mathematical difficulties. (iii) As it takes middle 50% terms hence it is a measure better than range. (iv) It is not affected by extreme terms as 25% of upper and 25% of lower terms are left out.
  • 13. Demerits or Limitations (i) As Q1 and Q3 are both positional measures hence are not capable of further algebraic treatment. (ii) Calculation are much more, but the result obtained is not of much importance. (iii) It is too much affected by fluctuations of sample.
  • 14. (iv) 50% terms play no role, first and last 25% items ignored may not give reliable result. (v) If the values are irregular, then result is affected badly.
  • 15. Mean Deviation Mean Deviation of a set of observations of a series is the arithmetic mean of all the deviations, without their algebraic signs, taken from its central value. Mean Deviation = Coefficient of Mean Deviation = N D f  x n o i t a i v e D n a e M
  • 16. Merits or Uses (i) As in case of , every term is taken in account. Hence it is certainly a better measure than other measures of dispersion. (ii) Mean deviation is extensively used in other fields such as Economics, Business, Commerce or any other field of such type. x
  • 17. (iii) It has least sampling fluctuations as compared to Range, Percentile and Quartile Deviation. (iv) When Comparison is needed this is perhaps the best measure. (v) Mean Deviation is rigidly defined.
  • 18. Standard Deviation It is defined as the square root of the mean of the squared deviation from the actual mean. It is also called the root mean square deviation. S.D. = Coefficient of S.D. = N x x   2 ) ( x 
  • 19. Variance It is the square of standard deviation. Variance = σ 2 Coefficient of Variance It is used to find the relative change that is said to exist in two or more series. C.V = 100  x 
  • 20. Merits or Uses (i) This is the most rigidly defined measure of dispersion and therefore is dependable. (ii) It is further capable of algebraic treatment. (iii) It is based on all the terms or observations hence is more reliable.
  • 21. Demerits or Limitations (i) As compared with other measures of dispersion it is more difficult to compute and not so easy to understand. (ii) In the case of open end intervals we have to make the assumption of lower limit of first interval and upper limit of last interval
  • 22. (iii) As far as S.D. is concerned it does not compare two series itself. We have to proceed to coefficient of S.D. or C.V. for this purpose. (iv) The extreme terms make the impact two much, therefore in some cases coefficient of Q.D. or of M.D. has a certain edge over it. If extreme item differ largely, then they make a heavy change when deviations are squared.