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Dispersion stati

1. 1. Measures of Dispersion Prepared By: Dr. N.V. Ravi, Sr. Executive Officer, BOS, ICAI. Quantitative Aptitude & Business Statistics
2. 2. Why Study Dispersion?An average, such as the meanor the median only locates thecentre of the data.An average does not tell usanything about the spread ofthe data. Quantitative Aptitude & Business Statistics: Measures of Dispersion 2
3. 3. What is DispersionDispersion ( also known asScatter ,spread or variation )measures the items vary fromsome central value .It measures the degree ofvariation. Quantitative Aptitude & Business Statistics: Measures of Dispersion 3
4. 4. Significance of Measuring DispersionTo determine the reliability ofan average.To facilitate comparison.To facilitate control.To facilitate the use of otherstatistical measures. Quantitative Aptitude & Business Statistics: Measures of Dispersion 4
5. 5. Properties of Good Measure of Dispersion Simple to understand and easy to calculate Rigidly defined Based on all items A meanable to algebraic treatment Sampling stability Not unduly affected by Extreme items. Quantitative Aptitude & Business Statistics: Measures of Dispersion 5
6. 6. Absolute Measure of Dispersion Based on selected Based on all items items 1.Range 1.Mean Deviation2.Inter Quartile Range 2.Standard Deviation Quantitative Aptitude & Business Statistics: Measures of Dispersion 6
7. 7. Relative measures of DispersionBased on Based onSelected all itemsitems1.Coefficient of 1.Coefficient of MDRange 2.Coefficient of SD &2.Coefficient of Coefficient of Variation Quantitative Aptitude & Business Statistics:QD Measures of Dispersion 7
8. 8. A small value for a measure ofdispersion indicates that the dataare clustered closely (the mean istherefore representative of the data).A large measure of dispersionindicates that the mean is notreliable (it is not representative ofthe data). Quantitative Aptitude & Business Statistics: Measures of Dispersion 8
9. 9. The RangeThe simplest measure ofdispersion is the range.For ungrouped data, therange is the differencebetween the highest andlowest values in a set ofdata. Quantitative Aptitude & Business Statistics: Measures of Dispersion 9
10. 10. RANGE = Highest Value -Lowest Value Quantitative Aptitude & Business Statistics: Measures of Dispersion 10
11. 11. The range only takes intoaccount the most extremevalues.This may not berepresentative of thepopulation. Quantitative Aptitude & Business Statistics: Measures of Dispersion 11
12. 12. The Range Example A sample of five accountinggraduates revealed thefollowing starting salaries:22,000,28,000, 31,000,23,000, 24,000.The range is 31,000 - 22,000= 9,000. Quantitative Aptitude & Business Statistics: Measures of Dispersion 12
13. 13. Coefficient of RangeCoefficient of Range iscalculated as,Coefficient of Range = L − S L + S = 0 . 1698 Quantitative Aptitude & Business Statistics: Measures of Dispersion 13
14. 14. From the following data calculate Range and Coefficient of RangeMarks 5 15 25 35 45 55No .of 10 20 30 50 40 30Students Quantitative Aptitude & Business Statistics: Measures of Dispersion 14
15. 15. Largest term (L)=55,Smallest term (S)=5Range=L-S=55-5=50Coefficient of Range L − S 55 − 5 = = = 0.833 L + S 55 + 5 Quantitative Aptitude & Business Statistics: Measures of Dispersion 15
16. 16. From the following data ,calculate Range and Coefficient of RangeMarks 0-10 10-20 20-30 30-40 40-50 50-60No .of 10 20 30 50 40 30Students Quantitative Aptitude & Business Statistics: Measures of Dispersion 16
17. 17. Lower limit of lowest class(S)=0Upper limit of highest class(L)=60Coefficient of Range L − S 60− 0 = = = 1.000 L + S 60+ 0 Quantitative Aptitude & Business Statistics: Measures of Dispersion 17
18. 18. Merits Of Range1.Its easy to understand andeasy to calculate.2.It does not require anyspecial knowledge.3.It takes minimum time tocalculate the value of Range. Quantitative Aptitude & Business Statistics: Measures of Dispersion 18
19. 19. Limitations of RangeIt does not take intoaccount of all items ofdistribution.Only two extreme values aretaken into consideration.It is affected by extremevalues. Quantitative Aptitude & Business Statistics: Measures of Dispersion 19
20. 20. Limitations of RangeIt does not indicate thedirection of variability.It does not present veryaccurate picture of thevariability. Quantitative Aptitude & Business Statistics: Measures of Dispersion 20
21. 21. Uses of RangeIt facilitates to study qualitycontrol.It facilitates to study variationsof prices on shares ,debentures,bonds and agriculturalcommodities.It facilitates weather forecasts. Quantitative Aptitude & Business Statistics: Measures of Dispersion 21
22. 22. Interquartile RangeThe interquartile range isused to overcome theproblem of outlyingobservations.The interquartile rangemeasures the range of themiddle (50%) values only Quantitative Aptitude & Business Statistics: Measures of Dispersion 22
23. 23. Inter quartile range = Q3 – Q1It is sometimes referred toas the quartile deviation orthe semi-inter quartilerange. Quantitative Aptitude & Business Statistics: Measures of Dispersion 23
24. 24. ExerciseThe number of complaintsreceived by the manager ofa supermarket wasrecorded for each of thelast 10 working days.21, 15, 18, 5, 10, 17, 21,19, 25 & 28 Quantitative Aptitude & Business Statistics: Measures of Dispersion 24
25. 25. Interquartile Range Example Sorted data5, 10, 15, 17, 18, 19, 21,21, 25 & 28 Quantitative Aptitude & Business Statistics: Measures of Dispersion 25
26. 26. N +1Q1 = 4 11Q1 = 4Q1 = 2 .75= 2 item + 0 .75 (15 − 10 )= 10 + 3 .75 = 13 .75 Quantitative Aptitude & Business Statistics: Measures of Dispersion 26
27. 27. 3( N + 1)Q3 = 4 33Q3 = 4Q3 = 8.25 = 8 + 0.25(9thitem − 8thitem)= 21 + 0.25(25 − 21)= 21 + 0.25(4) = 23 Quantitative Aptitude & Business Statistics: Measures of Dispersion 27
28. 28. Inter quartile range = 23 – 13.75 = 9.25 Co-efficient of Quartile Deviation = Q3 − Q1 = Q3 + Q1 = 0.1979 Quantitative Aptitude & Business Statistics: Measures of Dispersion 28
29. 29. From the following data ,calculate Inter Quartile Range and Coefficient of Quartile DeviationMarks 0- 10- 20- 30- 40- 50- 10 20 30 40 50 60No .ofStudents 10 20 30 50 40 30 Quantitative Aptitude & Business Statistics: Measures of Dispersion 29
30. 30. Calculation of Cumulative frequencies Marks No. of Cumulative Students Frequencies 0-10 10 10 10-20 20 30 cf 20-30 30f 60Q1 ClassL1 30-40 50 110 cf 40-50 40 f 150Q3Class 50-60 30 180 L3 180 Quantitative Aptitude & Business Statistics: Measures of Dispersion 30
31. 31. Q1= Size of N/4th item = Size of180/4th item = 45th itemThere fore Q1 lies in the Class20-30 ⎛N ⎞ ⎜ − c.f ⎟ Q1 = L + ⎜ 4 ⎟× C ⎜ f ⎟ ⎜ ⎟ ⎝ ⎠ Quantitative Aptitude & Business Statistics: Measures of Dispersion 31
32. 32. ⎛ 180 ⎞ ⎜ − 30 ⎟Q 1 = 20 + ⎜ 4 ⎟ × 10 ⎜ 30 ⎟ ⎜ ⎟ ⎝ ⎠ ⎛ 15 ⎞= 20 + ⎜ ⎟ × 10 ⎝ 30 ⎠= 25 Quantitative Aptitude & Business Statistics: Measures of Dispersion 32
33. 33. Q3= Size of 3.N/4th item = Size of3.180/4th item = 135th itemThere fore Q3 lies in the Class40-50 ⎛ N ⎞ ⎜ 3. − c. f ⎟ Q3 = L + ⎜ 4 ⎟×C ⎜ ⎜ f ⎟ ⎟ ⎝ ⎠ Quantitative Aptitude & Business Statistics: Measures of Dispersion 33
34. 34. ⎛ 180 ⎞ ⎜ 3. − 110 ⎟Q 3 = 40 + ⎜ 4 ⎟ × 10 ⎜ 40 ⎟ ⎜ ⎟ ⎝ ⎠ ⎛ 25 ⎞= 40 + ⎜ ⎟ × 10 ⎝ 10 ⎠= 46.25 Quantitative Aptitude & Business Statistics: Measures of Dispersion 34
35. 35. Inter Quartile Range=Q3-Q1 =46.25-25=21.25Coefficient of Quartile Deviation Q 3 − Q1 = =0.2982 Q 3 + Q1 Quantitative Aptitude & Business Statistics: Measures of Dispersion 35
36. 36. Merits Of Quartile DeviationIts easy to understand and easyto calculate.It is least affected by extremevalues.It can be used in open-endfrequency distribution. Quantitative Aptitude & Business Statistics: Measures of Dispersion 36
37. 37. Limitations of Quartile DeviationIt is not suited to algebraictreatmentIt is very much affected by samplingfluctuationsThe method of Dispersion is notbased on all the items of the series .It ignores the 50% of thedistribution. Quantitative Aptitude & Business Statistics: Measures of Dispersion 37
38. 38. Mean DeviationThe mean deviation takes intoconsideration all of the valuesMean Deviation: The arithmeticmean of the absolute values ofthe deviations from thearithmetic mean Quantitative Aptitude & Business Statistics: Measures of Dispersion 38
39. 39. MD = ∑ x− x nWhere: X = the value of eachobservation X = the arithmeticmean of the valuesn = the number of observations|| = the absolute value (the signs ofthe deviations are disregarded) Quantitative Aptitude & Business Statistics: Measures of Dispersion 39
40. 40. Mean Deviation ExampleThe weights of a sample of cratescontaining books for the bookstore are(in kgs.) 103, 97, 101, 106, 103.X = 510/5 = 102 kgs.Σ |x-x| = 1+5+1+4+1=12MD = 12/5 = 2.4Typically, the weights of the crates are2.4 kgs. from the mean weight of 102 kgs. Quantitative Aptitude & Business Statistics: Measures of Dispersion 40
41. 41. Frequency Distribution Mean Deviation If the data are in the form of a frequency distribution, the mean deviation can be calculated using the following formula: _ MD = ∑ f |x−x| ∑ fWhere f = the frequency of an observation xn = Σf = the sum of the frequencies Quantitative Aptitude & Business Statistics: Measures of Dispersion 41
42. 42. Frequency Distribution MD Example Number ofoutstanding Frequency fx |x-x| f|x-x| accounts 0 1 0 2 2 1 9 9 1 9 2 7 14 0 0 3 3 9 1 3 4 4 16 2 8 Total: 24 Σfx Σ f|x-x| = = 48 22 Quantitative Aptitude & Business Statistics: Measures of Dispersion 42
43. 43. _ x= ∑ fx ∑f mean = 48/24 = 2 _MD = ∑ f |x−x| ∑ fMD = 22/24 = 0.92 Quantitative Aptitude & Business Statistics: Measures of Dispersion 43
44. 44. Calculate Mean Deviation and Coefficient of Mean Deviation Marks No. of Cumulative (X) Students Frequencies 0-10 10 10 10-20 20 30 20-30 30 60 cf 30-40 50 f 110 40-50 40 150 Median 50-60 30 180 ClassL 180 Quantitative Aptitude & Business Statistics: Measures of Dispersion 44
45. 45. Calculation of Mean deviations from Median N 180 = 2 2 =90th itemMedian in Class =30-40,L=30,c.f=60,f=50 and c=10 Quantitative Aptitude & Business Statistics: Measures of Dispersion 45
46. 46. ⎛ N ⎞ ⎜ − c .f ⎟M =L+ ⎜ 2 ⎟×c ⎜ f ⎟ ⎜ ⎟ ⎝ ⎠ ⎛ 180 ⎞ ⎜ − 30 ⎟= 30 + ⎜ 2 ⎟ × 10 ⎜ 50 ⎟ ⎜ ⎟ ⎝ ⎠= 30 + 6 = 36 Quantitative Aptitude & Business Statistics: Measures of Dispersion 46
47. 47. Calculation of Mean Deviation of MedianMean Deviation from Median = ∑f x−M N 2040 = = 11 . 333 180 Quantitative Aptitude & Business Statistics: Measures of Dispersion 47
48. 48. Coefficient of MeanDeviation MeanDeviat ion = Median 11.333 = = 0.3148 36 Quantitative Aptitude & Business Statistics: Measures of Dispersion 48
49. 49. Merits of Mean DeviationIt is easy to understandIt is based on all items of theseriesIt is less affected by extremevaluesIt is useful small samples whenno detailed analysis is required. Quantitative Aptitude & Business Statistics: Measures of Dispersion 49
50. 50. Limitations of Mean DeviationIt lacks properties such that(+) and(-)signs which are nottaken into consideration.It is not suitable formathematical treatment. Quantitative Aptitude & Business Statistics: Measures of Dispersion 50
51. 51. It may not give accurateresults when the degree ofvariability in a series is veryhigh. Quantitative Aptitude & Business Statistics: Measures of Dispersion 51
52. 52. Standard DeviationStandard deviation is the mostcommonly used measure ofdispersionSimilar to the mean deviation,the standard deviation takesinto account the value of everyobservation Quantitative Aptitude & Business Statistics: Measures of Dispersion 52
53. 53. The values of the meandeviation and the standarddeviation should be relativelysimilar. Quantitative Aptitude & Business Statistics: Measures of Dispersion 53
54. 54. Standard DeviationThe standard deviation uses thesquares of the residualsSteps; Find the sum of the squares of the residuals Find the mean Then take the square root of the mean Quantitative Aptitude & Business Statistics: Measures of Dispersion 54
55. 55. 2 ⎛ ⎞ _ ∑⎜ x − x ⎟ ⎝ ⎠σ= N Quantitative Aptitude & Business Statistics: Measures of Dispersion 55
56. 56. From the following data calculateStandard Deviation5,15,25,35,45 and 55 X= ∑X X= 180 = 30 N 6 Quantitative Aptitude & Business Statistics: Measures of Dispersion 56
57. 57. σ= ∑ (X − X ) 2 N 1750= = 17 .078 6 Quantitative Aptitude & Business Statistics: Measures of Dispersion 57
58. 58. Frequency Distribution SDIf the data are in the form of a frequencydistribution the standard deviation is given by σ= ∑ f.(X − X) 2 N ∑ ∑ 2 f .x 2 ⎛ f .x ⎞ = −⎜ ⎟ N ⎜ N ⎟ ⎝ ⎠ Quantitative Aptitude & Business Statistics: Measures of Dispersion 58
59. 59. From the following data ,calculate Standard Deviation . Marks 5 15 25 35 45 55 (X) No. of 10 20 30 50 40 30Students (f) Quantitative Aptitude & Business Statistics: Measures of Dispersion 59
60. 60. Mean = X= ∑f.x = 6300= 35 N 180 Quantitative Aptitude & Business Statistics: Measures of Dispersion 60
61. 61. Marks No. of (X- fx2(X) Students 35)=x (f) 5 10 -30 9000 15 20 -20 8000 25 30 -10 3000 35 50 0 0 45 40 10 4000 55 30 20 12000 N=180 ∑fx2 Quantitative Aptitude & Business Statistics: Measures of Dispersion =3600061
62. 62. ∑ ∑ 2 f.x 2 ⎛ f.x ⎞σ= −⎜ ⎟ N ⎜ N ⎟ ⎝ ⎠= ∑ f.x − (X ) 2 2 =14.142 N Quantitative Aptitude & Business Statistics: Measures of Dispersion 62
63. 63. Properties of Standard DeviationIndependent of change of originNot independent of change of Scale.Fixed Relationship among measuresof Dispersion. Quantitative Aptitude & Business Statistics: Measures of Dispersion 63
64. 64. In a normal distribution there is fixed relationship 2 QD = σ 3 4 MD = σ 5 Thus SD is neverAptitude & Business Statistics: and MD Quantitative less than QD Measures of Dispersion 64
65. 65. Bell - Shaped Curve showing the relationship between σ and μ . 68.27% 95.45% 99.73% μ−3σ μ−2σ μ−1σ μ μ+1σ μ+2σ μ+ 3σ Quantitative Aptitude & Business Statistics: Measures of Dispersion 65
66. 66. Minimum sum of Squares; The Sum ofSquares of Deviations of items in theseries from their arithmetic mean isminimum.Standard Deviation of n natural numbers 2 N −1 = 12 Quantitative Aptitude & Business Statistics: Measures of Dispersion 66
67. 67. Combined standard deviation 2 2 2 2 N1σ1 +N2σ2 +N1d1 +N2d2 σ12 = N1 +N2 Quantitative Aptitude & Business Statistics: Measures of Dispersion 67
68. 68. Where σ12 =Combined standard Deviation oftwo groups σ 1 =Standard Deviation of first groupN1=No. of items of First groupN2=No. of items of Second group σ2 = Standard deviation of Second group Quantitative Aptitude & Business Statistics: Measures of Dispersion 68
69. 69. d1 = X 1 − X 12d2 = X2 − X12 Where X 12 is the combined mean of two groups Quantitative Aptitude & Business Statistics: Measures of Dispersion 69
70. 70. Merits of Standard DeviationIt is based on all the items ofthe distribution.it is a meanable to algebraictreatment since actual + or –signs deviations are taken intoconsideration.It is least affected byfluctuations of sampling Quantitative Aptitude & Business Statistics: Measures of Dispersion 70
71. 71. Merits of Standard DeviationIt facilitates the calculation ofcombined standard Deviation andCoefficient of Variation ,which isused to compare the variability oftwo or more distributionsIt facilitates the other statisticalcalculations like skewness,correlation.it provides a unit of measurement forthe normal distribution. Quantitative Aptitude & Business Statistics: Measures of Dispersion 71
72. 72. Limitations of Standard DeviationIt can’t be used for comparingthe variability of two or moreseries of observations given indifferent units. A coefficient ofStandard deviation is to becalculated for this purpose.It is difficult to compute andcompared Quantitative Aptitude & Business Statistics: Measures of Dispersion 72
73. 73. Limitations of Standard Deviation It is very much affected by the extreme values. The standard deviation can not be computed for a distribution with open-end classes. Quantitative Aptitude & Business Statistics: Measures of Dispersion 73
74. 74. VarianceVariance is the arithmetic mean ofthe squares of deviations of all theitems of the distributions fromarithmetic mean .In other words,variance is the square of theStandard deviation= 2 σVariance= σ= var iance Quantitative Aptitude & Business Statistics: Measures of Dispersion 74
75. 75. Interpretation of VarianceSmaller the variance,greater the uniformity inpopulation.Larger the variance ,greaterthe variability Quantitative Aptitude & Business Statistics: Measures of Dispersion 75
76. 76. The Coefficient of VariationThe coefficient of variation is ameasure of relative variability It is used to measure the changes that have taken place in a population over time Quantitative Aptitude & Business Statistics: Measures of Dispersion 76
77. 77. To compare the variability oftwo populations that areexpressed in different units ofmeasurementIt is expressed as apercentage Quantitative Aptitude & Business Statistics: Measures of Dispersion 77
78. 78. Formula: σ Where: CV = × 100 X X = meanσ = standard deviation Quantitative Aptitude & Business Statistics: Measures of Dispersion 78
79. 79. 1. Dispersion measures(a) The scatter ness of a set of observations(b) The concentration of set of observations( c) The Peaked ness of distribution (d) None Quantitative Aptitude & Business Statistics: Measures of Dispersion 79
80. 80. 1. Dispersion measures(a) The scatter ness of a set of observations(b) The concentration of set of observations( c) The Peaked ness of distribution (d) None Quantitative Aptitude & Business Statistics: Measures of Dispersion 80
81. 81. 2. Which one is an absolute measure of Dispersion? (a) Range (b) Mean Deviation ( c) Quartile Deviation( d) all these measures Quantitative Aptitude & Business Statistics: Measures of Dispersion 81
82. 82. 2. Which one is an absolute measure of Dispersion? (a) Range (b) Mean Deviation ( c) Quartile Deviation( d) all these measures Quantitative Aptitude & Business Statistics: Measures of Dispersion 82
83. 83. 3.Which measures of Dispersion is not affected by the presence of extreme observations (a) deviation (b) Quartile Deviation (C) Mean Deviation(d) Range Quantitative Aptitude & Business Statistics: Measures of Dispersion 83
84. 84. 3.Which measures of Dispersion is not affected by the presence of extreme observations (a) deviation (b) Quartile Deviation (C) Mean Deviation(d) Range Quantitative Aptitude & Business Statistics: Measures of Dispersion 84
85. 85. 3.Which measures of Dispersion is not affected by the presence of extreme observations (a) deviation (b) Quartile Deviation (C) Mean Deviation(d) Range Quantitative Aptitude & Business Statistics: Measures of Dispersion 85
86. 86. 4.which measures of Dispersion is based on all the items of observations(a) Mean Deviation(b) Standard Deviation(C) Quartile Deviation(d) a and b but not c Quantitative Aptitude & Business Statistics: Measures of Dispersion 86
87. 87. 4.which measures of Dispersion is based on all the items of observations(a) Mean Deviation(b) Standard Deviation(C) Quartile Deviation(d) a and b but not c Quantitative Aptitude & Business Statistics: Measures of Dispersion 87
88. 88. 5.Standard Deviation is(a) absolute measure(b) relative measure(c) both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 88
89. 89. 5.Standard Deviation is(a) absolute measure(b) relative measure(c) both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 89
90. 90. 6.Coefficient of standard deviation is(a) SD/mean(b) SD/Median(c) SD/Mode (d) Mean/SD Quantitative Aptitude & Business Statistics: Measures of Dispersion 90
91. 91. 6.Coefficient of standard deviation is(a) SD/mean(b) SD/Median(c) SD/Mode (d) Mean/SD Quantitative Aptitude & Business Statistics: Measures of Dispersion 91
92. 92. 7.Coefficient of Quartile Deviation iscalculated by formula(a)(Q3-Q1)/4(b) (Q3-Q1)/2 (c) (Q3-Q1)/(Q3+Q1)(d) (Q3+Q1)/(Q3-Q1 Quantitative Aptitude & Business Statistics: Measures of Dispersion 92
93. 93. 7.Coefficient of Quartile Deviation iscalculated by formula(a)(Q3-Q1)/4(b) (Q3-Q1)/2 (c) (Q3-Q1)/(Q3+Q1)(d) (Q3+Q1)/(Q3-Q1 Quantitative Aptitude & Business Statistics: Measures of Dispersion 93
94. 94. 8.The standard Deviation of5,8,5,5,5,8and 8 is(a) 4(b) 6(C) 3(d) 0 Quantitative Aptitude & Business Statistics: Measures of Dispersion 94
95. 95. 8.The standard Deviation of5,8,5,5,5,8and 8 is(a) 4(b) 6(C) 3(d) 0 Quantitative Aptitude & Business Statistics: Measures of Dispersion 95
96. 96. 9.If all the observations are increased by 10,then(a) SD would be increased by 10(b)Mean deviation would be increased by 10 ( c) Quartile Deviation would be increased by 10 (d) all these remain unchanged Quantitative Aptitude & Business Statistics: Measures of Dispersion 96
97. 97. 9.If all the observations are increased by 10,then(a) SD would be increased by 10(b)Mean deviation would be increased by 10 ( c) Quartile Deviation would be increased by 10 (d) all these remain unchanged Quantitative Aptitude & Business Statistics: Measures of Dispersion 97
98. 98. 10.For any two numbers SD is always(a) Twice the range(b) Half of the range© Square of range(d) none of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 98
99. 99. 10.For any two numbers SD is always(a) Twice the range(b) Half of the range© Square of range(d) none of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 99
100. 100. 11Mean deviation is minimum whendeviations are taken about(a) Arithmetic Mean(b) Geometric Mean© Harmonic Mean(d) Median Quantitative Aptitude & Business Statistics: Measures of Dispersion 100
101. 101. 11.Mean deviation is minimum whendeviations are taken about(a) Arithmetic Mean(b) Geometric Mean© Harmonic Mean(d) Median Quantitative Aptitude & Business Statistics: Measures of Dispersion 101
102. 102. 12.Root mean square deviation is(a) Standard Deviation(b) Quartile Deviation© both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 102
103. 103. 12.Root mean square deviation frommean is(a) Standard Deviation(b) Quartile Deviation© both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 103
104. 104. 13.Standard Deviation is(a) Smaller than mean deviation aboutmean(b) Smaller than mean deviation aboutmedian© Larger than mean deviation about mean(d) none of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 104
105. 105. 13.Standard Deviation is(a) Smaller than mean deviation aboutmean(b) Smaller than mean deviation aboutmedian© Larger than mean deviation about mean(d) none of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 105
106. 106. 14.Is least affected by samplingfluctuationsa) Standard Deviation(b) Quartile Deviation© both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 106
107. 107. 14.Is least affected by samplingfluctuationsa) Standard Deviation(b) Quartile Deviation© both(d) none Quantitative Aptitude & Business Statistics: Measures of Dispersion 107
108. 108. 15. Coefficient of variation of two series is 60%and 80% respectively. Their standard deviationsare 20 and 16 respectively, what is their A.MA) 15 and 20B) 33.3 and 20C) 33.3 and 15D) 12 and 12.8 Quantitative Aptitude & Business Statistics: Measures of Dispersion 108
109. 109. 15. Coefficient of variation of two series is 60%and 80% respectively. Their standard deviationsare 20 and 16 respectively, what is their A.MA) 15 and 20B) 33.3 and 20C) 33.3 and 15D) 12 and 12.8 Quantitative Aptitude & Business Statistics: Measures of Dispersion 109
110. 110. 16. For the numbers 1, 2, 3, 4, 5, 6, 7 standarddeviation is:A) 3B) 4C) 2D) None of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 110
111. 111. 16. For the numbers 1, 2, 3, 4, 5, 6, 7 standarddeviation is:A) 3B) 4C) 2D) None of these Quantitative Aptitude & Business Statistics: Measures of Dispersion 111
112. 112. THE ENDMeasures of Dispersion