SlideShare a Scribd company logo
1 of 16
Download to read offline
iarammati Nere Senttm
Hqramneti RafruentteniadaKim o Procoa
t oispl shdstinl Tem obtamad .totoet
olleed and bulated olata, visuly
mentad aapm. to undershnd
abetter uAYt up md onm wthin tho-
bgy admInisttr
ma_ConwTCia Seutr tuye of cliagrams
Vari 0diiaL_ Sds Slatifis ja esentias
t undersand ickly abrnt thaPrvre ou
A Fa i PietoriaL reretation o#
e a t i v hansb2tuumi twoqantHis
varie a a
Graphs and Curves
Line graph and curve
Suppose we have plotted some points with reference to two
perpendicular lines
as axesS,
32
D 28
D
/ B
E1
15
A
10
12
Curve
Line Graph
Fig. 9.5
Fig. 9.6
we will get the proper location of some points, which may be called as A, B, C, D, . . .
etc. Now, if wejoin AB, BC, CD,... by separate lines then we will get a line graph
(fig. 9.5.) and if we join the points A, B, C, D,.. .
by a suitable arch, so that the
turning points atB,C,D,. .
becomes sinooth, then we will get a 'curve' (fig. 9.6.).
Time series
Any series of data related with time is the time series. As for example, data on
Seasonal Variation of sales and purchase of certain commodities is the time series.
Yearly budget of central or any state government, day-wise attendance of students
in a class in a week, population according to census report are all the examples o
a. time series.
Any line graph related to time series is knowiu as
Historigram.
Historigrams may be of single, two or more variables. If the average monthly
income, expenditure and savings of a person are given for last ten years, then taking
any one of the data into account, We imay draw a single liistorigranm, or a double
historigram with twice of them or with all of tlhem a multi-historigram can be drawn.
Diagramniatic itefpresentation
209
E x a n n p
alnple 9.5. The average inonthiy income, exjpenditure and saviugs of a skilled
Luhour in a certain company are given 1or 10 years. Express the data graphically in
a s u i t a b l e m a n n e r .
Years Average monthly Average mouthly Average monthly
income expenditure savings
1989-90
1650 1275 375
1990-
1920 4S0 440
1991-92
2340 1620 r20
1992-93 2760 1975 783
1993-94 280 2250 1030
1994-95 6-40 2800 840
1995 7520 4450 3070
1996-997 12640 8500 1140
1997598 18580 2300 6280
1998-199 23200 14700 8500
Solution:
AVERAGE MONTHLY INCOME, EXPENDITURE AND SAVINGS OF A SKILLED LABOUA
25000
20000 Income
15000
- -D- Expenditure
10000
Savings
5000
9 -
1 9
9 0 - 9
2 . 9
9 9
1994-95
1995-9 -99
199
1998
Histograms of two or more variables
Fig.9.7
Example 9.6. First 8 batsnen of two teams in a cricket match scóred as following:
Batsman 1 2 3 4 5 6 7 S
Teain A 87 43 14 29 43 32 20 S
Team B 48 57 64 40 0 22 28 30
onare teani-wise performance by irawing line graph.
1991-92 1993-94 S6-97
1997-98
P'robabilaty aulStatisties
Solution:
RUNS SCORED BY FIRST 8 BATSMEN OF TWO TEAMS
00
90
TEAM A
70
- -TEAM B
0
0
Batting order of two teams
Fig. 9.8
Note: The above are the examples of line graphs but these are not the historigrams
as the data is not related with time.
Histogram
To
represent graphically. the frequency distribution of
corresponding class intervals,
the adjacent rectangular bars are used. The
assembly of such adjacent rectangular
bars are known as
Histogram. The length of the rectaugles are
proportional to
corresponding frequencies of classes. Karl PearsOu in 1895 first used this nane.
Types of histogramn
(1) Histogram for ecqual class intervals.
(2) Histogram for
unequal class
intervals
Methods of construction
(1) When the class intervals are cqual, the hight of the rectangles should be
proportional to the
corresponcding trequencies of cach class.
(2) If there be any discrete type ol class
intervals we arc to convert thenu to
continuous type.
(3) Generally class intervals are to be laken alog horizontal axis and frequ-
encies in äny form, along vertical axis.
(4) In case of histogram for inequal class intervals, the breadths of the rer-
tangles are to be taken
projortional to the class width and the heights of
the rectangles, proportional to
freqieney density ot the
respertive class.
3.45
3.24 HISTOGRAM
A Histogram is a
graplh containing a set of rectangles, each being constructedtorepresent the
size ofthe class interval by its width andthe frequency in each class-interval byits height. The area
of each rectangle is
proportional to the frequencyin the respective class-interval andthe total area
of the histogram is
proportionalto thetotal frequency. A
histogram is used to depicta frequency
distribution.
CUISuuu storam a
(mapl of rejuene Hctibt.an
Th ak, o4 equinty distibacitn are
deie t
Prelet he chatscrvistie feat ures D
ofigtribuuhions °aooding {hIY
mor req ny
Shape Ond
Th mat Conmmmly URed hs ae
DHistogra
foquany polm
C)Feqwnty Curwa
Cl) Cum 4tue reawny (ure
23. GRAPHIC REPRESENTATION OF A FREQUENCY DISTRIBUTION
It is often useful to represent a frequency distribution by means of a diagramn
which makes the unwieldy data intelligible and conveys to the eye the general run of
the observations. Diagrammatic representation also facilitates the
comparison of
two
or more frequency distributions. We consider below some important types of graphic
representation.
2.31. Histogram. In drawing the histogram of a given continuous frequency
dtstríbution we first mark off along the
x
-
axis all the class intervals
on a
suitabie
scale. On each class interval erect rectangles with heights proportional to the
frequency of the corresponding class interval so that the area of the rectangleis
proportional to the frequency of the class. It, however, the classes are of uncqual
width then the height of the rectangle will be proportional to the ratio of the
frequencies to the width of the classes. The diagram of continuous rectangles so
obtained is called histogran1.
l aictoTram for an ungrouped freauoncy distrib1ution of a variabic
T
Comprenensive Slatistical
Methods
TYPEL HISTOGRAM WITH EQUAL CLASS INIERVALS
The sizes of class intervals are drawn on I-axis with equal distances and their respe
Irequencies on y-axis. Class and its frequency taken together torm a
rectangle. The graph at
rectangles is known as
histogram.
Each class has lower and upper values. This gives us two equal ines
representing th
frequencies. Upper ends of the lines are joined together. This
process will give us
rectangles. Te
heights of the rectangles will be
proportional to their frequencies.
Example 36. The monthly profits in rupees of 100 shops distributed as follows:
Profit per shop 0-100 100-200 200300 300-400 400-500 500 600
No. of shops
pective
apa of
be
20 17
12 18 27
Solution. This is the case of
Histogram with equal frequencies.
30
0 100 200 300 400 500 600
Class-Interval [P rofit per shop
Fig. 3.41. Histogram showing monthly prolits.
Example 37.Draw the histogram for the
following data:
Marks
0-
10 10 20 20 30 30 40 40 50 50 60 60 -70
S0 40
No. of Students
Solution. We
represent the class limits along x-axis and
frequencies along y-axis. Taking class
intervals as bases and the
corresponding frequencies (No. of students) as
heights, we construct the
rectangles to
get the
histogram of the given frequency distribution as shown in Fig. 3.42.
20 30 70
0 40
Scale: Along x-axis 1 cm =
10 marks
Along y-a xis: 1 cm =
10 studenis
A
10 20 30 40 50 60 70
Marks-
Flg.3.42. Histogram showing marks oblained by sludents.
TYPE II.
HISTOGRAM WHEN CLASS INTERVALS ARE GIVEN N
EXCLUSI
FORM, i.e., WHEN CLASS
INTERVALS ARE NOT
CONTINUOUS
In a
histogram, it is
necessary that the
adjacent rectangles be attached to each other. If
w
to
represent the given data (in
cxCusivefomm) as such we shall get a bar
diagram as there w
gaps in between the classes. But in a
histogram the bars are
continuous without any Be
The histogram of the given data is given by Fig. 3.49.
Note: The crank mark or kink ( ) in the curve on the hornzontal axis means tha
lack of space this small distance representss to
S.
owing
he anu
Example 45. Draw the histogram of the following frequenc)y distribulion and show th
TYPETV HISTOGRAM WITH UNEQUAL CLASS INTERVALS
On your graph which represents the total number of wage-eamers in he age-group 19-n
35-
14 15 16- 17 18-20 21-24 25 29 30-34
0
00
Age group
150 i10 I10
No. of wage-earners 120 140
Solution. Here the class intervals have been marked by class-limits. As a result, the uperli
of one class does not coincide with the lower limit of the next
class. In order to draw a histogm
the upper limit of one class must coincide with the lower limit of the next class. To draw a histogm
n suchcase where the upper limit of one class does not coincide with the lower limit ofthene
class, class limits of all the classes should be extended to their class-boundaries. This ill elt
drawing ofa histogram from a
frequency distribution in which class intervals are marked byclas
limits.
In this example, the classes are not of equal width. Some have less width and some have
more width. So the histogram should be drawn on the basis of frequency density and not on te
basis of frequency.
Calculation of Histogram
Class-boundary Class-width
Frequency densiy
Frequency
(No. of wage-earners)
Class-interval
Age group)
13.5 15.5
15.5 17.5
17.5 20.5
(Age groupP)
14 15
120 0
16- 17
140 70
18- 20
150 0
21 24 20.5 24.5
10 27.5
25 -29 24.5 29.5
110 2
34 29.5 34.5
100 20
35 3 39 34.5 39.5
0 18
13.5 15.5 17.5 19 20.5 24.5 29.5 32 34.5 39.5
Class-boundary (Age In
years
Flg.3.50. Histogram showing the
number of
wage-eatners.
The total number of
wage earnerS in the age group 19 -32 is shown by the sn
in the histogram.
aded area
DiagraInmiatiC 1ieprescntation
211
Example 9.7. Construct a
Histogram tron the followino talla.
Weight (in lbs) No. of Men
95-105 105
105-115
210
115-125
125-135
300
175
135-145 255
Example 9.8. Draw a Histogram of the followingdata:
Height in cm No. of Persons
120-129 15
130-139 20
140-154 45
155-159 25
160-179 30
C o m p r e n E T o m
3.50
Example
42. The following
table presents
the number ofiterate females in the age pro
(10 34) in a town:
group
25-29 30-34
20-24
Age group
10-14
15-19
580 290
800
No. ofFemales : 300
980
Draw a histogram to represent the above data.
discontinuous distribution. In order to draw a histogram
autian. Thedifferenco
Diagrammatic and Graphic Presentation of Data
3.15
Example 14: The following figures relate to the costof construction of a huuse in Delhi:
Ttem :Cement Steel Bricks Timber Labour Miscellaneous
Expenditure 20% 18% 10% 15% 25% 12%
Represent the data by a suitablediagram.
3.14
he
Example 13: Draw a pie diagram to represeni ihefollowing data ofinvestmment patterm in the
Five Year Plan: 14%
Agricuiture andCommunity Development
16%
Irrigaiion and Power
Small and Organised Industries and Minerals
Transport and Communication
Social senvices
29%
17%
16%
8 9
Inventories
Example 15: Draw a suitable diagramforthe following:
Expenditure on item Percentage of Total expenditure
Food 65
Clothing 10
Housing 12
Fuel andlighting 5
Miscellaneous 8

More Related Content

Similar to Diagramatic Representation.pdf

Presentation of statistics
Presentation of statisticsPresentation of statistics
Presentation of statisticsJagdish Powar
 
Statistical Methods: Graphical Representation of Data
Statistical Methods: Graphical Representation of DataStatistical Methods: Graphical Representation of Data
Statistical Methods: Graphical Representation of DataDr. Ramkrishna Singh Solanki
 
PRESENTATION OF DATA.pptx
PRESENTATION OF DATA.pptxPRESENTATION OF DATA.pptx
PRESENTATION OF DATA.pptxajesh ps
 
Graphical representation of data mohit verma
Graphical representation of data mohit verma Graphical representation of data mohit verma
Graphical representation of data mohit verma MOHIT KUMAR VERMA
 
Ejercicio resuelto-de-estadc3adstica-descriptiva1
Ejercicio resuelto-de-estadc3adstica-descriptiva1Ejercicio resuelto-de-estadc3adstica-descriptiva1
Ejercicio resuelto-de-estadc3adstica-descriptiva1Sandra Hernández Cely
 
2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogivesmlong24
 
Histogram and historigram
Histogram and historigram Histogram and historigram
Histogram and historigram salihashaheen
 
Statistics
StatisticsStatistics
Statisticsitutor
 
AIOU Code 1430 Solved Assignments Autumn 2022.pptx
AIOU Code 1430 Solved Assignments Autumn 2022.pptxAIOU Code 1430 Solved Assignments Autumn 2022.pptx
AIOU Code 1430 Solved Assignments Autumn 2022.pptxZawarali786
 
Qt graphical representation of data
Qt   graphical representation of dataQt   graphical representation of data
Qt graphical representation of dataJoel Pais
 
Qt graphical representation of data
Qt   graphical representation of dataQt   graphical representation of data
Qt graphical representation of dataJoel Pais
 
3_-frequency_distribution.pptx
3_-frequency_distribution.pptx3_-frequency_distribution.pptx
3_-frequency_distribution.pptxitzsudipto99
 
Plotting histogram in bigdata analytics
Plotting histogram in bigdata analyticsPlotting histogram in bigdata analytics
Plotting histogram in bigdata analyticsRajalakshmiK19
 
135. Graphic Presentation
135. Graphic Presentation135. Graphic Presentation
135. Graphic PresentationLAKSHMANAN S
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-datamariantuvilla
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-datalawrencechavenia
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-datalovelyquintero
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-datalovelyquintero
 

Similar to Diagramatic Representation.pdf (20)

Presentation of statistics
Presentation of statisticsPresentation of statistics
Presentation of statistics
 
Statistical Methods: Graphical Representation of Data
Statistical Methods: Graphical Representation of DataStatistical Methods: Graphical Representation of Data
Statistical Methods: Graphical Representation of Data
 
PRESENTATION OF DATA.pptx
PRESENTATION OF DATA.pptxPRESENTATION OF DATA.pptx
PRESENTATION OF DATA.pptx
 
Frequency Polygon
Frequency PolygonFrequency Polygon
Frequency Polygon
 
Graphical representation of data mohit verma
Graphical representation of data mohit verma Graphical representation of data mohit verma
Graphical representation of data mohit verma
 
Unit 3 Statistics
Unit 3 Statistics Unit 3 Statistics
Unit 3 Statistics
 
Ejercicio resuelto-de-estadc3adstica-descriptiva1
Ejercicio resuelto-de-estadc3adstica-descriptiva1Ejercicio resuelto-de-estadc3adstica-descriptiva1
Ejercicio resuelto-de-estadc3adstica-descriptiva1
 
2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives
 
Histogram and historigram
Histogram and historigram Histogram and historigram
Histogram and historigram
 
Statistics
StatisticsStatistics
Statistics
 
AIOU Code 1430 Solved Assignments Autumn 2022.pptx
AIOU Code 1430 Solved Assignments Autumn 2022.pptxAIOU Code 1430 Solved Assignments Autumn 2022.pptx
AIOU Code 1430 Solved Assignments Autumn 2022.pptx
 
Qt graphical representation of data
Qt   graphical representation of dataQt   graphical representation of data
Qt graphical representation of data
 
Qt graphical representation of data
Qt   graphical representation of dataQt   graphical representation of data
Qt graphical representation of data
 
3_-frequency_distribution.pptx
3_-frequency_distribution.pptx3_-frequency_distribution.pptx
3_-frequency_distribution.pptx
 
Plotting histogram in bigdata analytics
Plotting histogram in bigdata analyticsPlotting histogram in bigdata analytics
Plotting histogram in bigdata analytics
 
135. Graphic Presentation
135. Graphic Presentation135. Graphic Presentation
135. Graphic Presentation
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-data
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-data
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-data
 
Presentation and-analysis-of-business-data
Presentation and-analysis-of-business-dataPresentation and-analysis-of-business-data
Presentation and-analysis-of-business-data
 

Recently uploaded

Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxNirmalaLoungPoorunde1
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docxPoojaSen20
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon AUnboundStockton
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsanshu789521
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentInMediaRes1
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 

Recently uploaded (20)

Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docx
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
 
Staff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSDStaff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSD
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha elections
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media Component
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 

Diagramatic Representation.pdf

  • 1. iarammati Nere Senttm Hqramneti RafruentteniadaKim o Procoa t oispl shdstinl Tem obtamad .totoet olleed and bulated olata, visuly mentad aapm. to undershnd abetter uAYt up md onm wthin tho- bgy admInisttr ma_ConwTCia Seutr tuye of cliagrams Vari 0diiaL_ Sds Slatifis ja esentias t undersand ickly abrnt thaPrvre ou
  • 2. A Fa i PietoriaL reretation o# e a t i v hansb2tuumi twoqantHis varie a a
  • 3. Graphs and Curves Line graph and curve Suppose we have plotted some points with reference to two perpendicular lines as axesS, 32 D 28 D / B E1 15 A 10 12 Curve Line Graph Fig. 9.5 Fig. 9.6 we will get the proper location of some points, which may be called as A, B, C, D, . . . etc. Now, if wejoin AB, BC, CD,... by separate lines then we will get a line graph (fig. 9.5.) and if we join the points A, B, C, D,.. . by a suitable arch, so that the turning points atB,C,D,. . becomes sinooth, then we will get a 'curve' (fig. 9.6.). Time series Any series of data related with time is the time series. As for example, data on Seasonal Variation of sales and purchase of certain commodities is the time series. Yearly budget of central or any state government, day-wise attendance of students in a class in a week, population according to census report are all the examples o a. time series. Any line graph related to time series is knowiu as Historigram. Historigrams may be of single, two or more variables. If the average monthly income, expenditure and savings of a person are given for last ten years, then taking any one of the data into account, We imay draw a single liistorigranm, or a double historigram with twice of them or with all of tlhem a multi-historigram can be drawn.
  • 4. Diagramniatic itefpresentation 209 E x a n n p alnple 9.5. The average inonthiy income, exjpenditure and saviugs of a skilled Luhour in a certain company are given 1or 10 years. Express the data graphically in a s u i t a b l e m a n n e r . Years Average monthly Average mouthly Average monthly income expenditure savings 1989-90 1650 1275 375 1990- 1920 4S0 440 1991-92 2340 1620 r20 1992-93 2760 1975 783 1993-94 280 2250 1030 1994-95 6-40 2800 840 1995 7520 4450 3070 1996-997 12640 8500 1140 1997598 18580 2300 6280 1998-199 23200 14700 8500 Solution: AVERAGE MONTHLY INCOME, EXPENDITURE AND SAVINGS OF A SKILLED LABOUA 25000 20000 Income 15000 - -D- Expenditure 10000 Savings 5000 9 - 1 9 9 0 - 9 2 . 9 9 9 1994-95 1995-9 -99 199 1998 Histograms of two or more variables Fig.9.7 Example 9.6. First 8 batsnen of two teams in a cricket match scóred as following: Batsman 1 2 3 4 5 6 7 S Teain A 87 43 14 29 43 32 20 S Team B 48 57 64 40 0 22 28 30 onare teani-wise performance by irawing line graph. 1991-92 1993-94 S6-97 1997-98
  • 5. P'robabilaty aulStatisties Solution: RUNS SCORED BY FIRST 8 BATSMEN OF TWO TEAMS 00 90 TEAM A 70 - -TEAM B 0 0 Batting order of two teams Fig. 9.8 Note: The above are the examples of line graphs but these are not the historigrams as the data is not related with time. Histogram To represent graphically. the frequency distribution of corresponding class intervals, the adjacent rectangular bars are used. The assembly of such adjacent rectangular bars are known as Histogram. The length of the rectaugles are proportional to corresponding frequencies of classes. Karl PearsOu in 1895 first used this nane. Types of histogramn (1) Histogram for ecqual class intervals. (2) Histogram for unequal class intervals Methods of construction (1) When the class intervals are cqual, the hight of the rectangles should be proportional to the corresponcding trequencies of cach class. (2) If there be any discrete type ol class intervals we arc to convert thenu to continuous type. (3) Generally class intervals are to be laken alog horizontal axis and frequ- encies in äny form, along vertical axis. (4) In case of histogram for inequal class intervals, the breadths of the rer- tangles are to be taken projortional to the class width and the heights of the rectangles, proportional to freqieney density ot the respertive class.
  • 6. 3.45 3.24 HISTOGRAM A Histogram is a graplh containing a set of rectangles, each being constructedtorepresent the size ofthe class interval by its width andthe frequency in each class-interval byits height. The area of each rectangle is proportional to the frequencyin the respective class-interval andthe total area of the histogram is proportionalto thetotal frequency. A histogram is used to depicta frequency distribution. CUISuuu storam a
  • 7. (mapl of rejuene Hctibt.an Th ak, o4 equinty distibacitn are deie t Prelet he chatscrvistie feat ures D ofigtribuuhions °aooding {hIY mor req ny Shape Ond Th mat Conmmmly URed hs ae DHistogra foquany polm C)Feqwnty Curwa Cl) Cum 4tue reawny (ure
  • 8. 23. GRAPHIC REPRESENTATION OF A FREQUENCY DISTRIBUTION It is often useful to represent a frequency distribution by means of a diagramn which makes the unwieldy data intelligible and conveys to the eye the general run of the observations. Diagrammatic representation also facilitates the comparison of two or more frequency distributions. We consider below some important types of graphic representation. 2.31. Histogram. In drawing the histogram of a given continuous frequency dtstríbution we first mark off along the x - axis all the class intervals on a suitabie scale. On each class interval erect rectangles with heights proportional to the frequency of the corresponding class interval so that the area of the rectangleis proportional to the frequency of the class. It, however, the classes are of uncqual width then the height of the rectangle will be proportional to the ratio of the frequencies to the width of the classes. The diagram of continuous rectangles so obtained is called histogran1. l aictoTram for an ungrouped freauoncy distrib1ution of a variabic T
  • 9. Comprenensive Slatistical Methods TYPEL HISTOGRAM WITH EQUAL CLASS INIERVALS The sizes of class intervals are drawn on I-axis with equal distances and their respe Irequencies on y-axis. Class and its frequency taken together torm a rectangle. The graph at rectangles is known as histogram. Each class has lower and upper values. This gives us two equal ines representing th frequencies. Upper ends of the lines are joined together. This process will give us rectangles. Te heights of the rectangles will be proportional to their frequencies. Example 36. The monthly profits in rupees of 100 shops distributed as follows: Profit per shop 0-100 100-200 200300 300-400 400-500 500 600 No. of shops pective apa of be 20 17 12 18 27 Solution. This is the case of Histogram with equal frequencies. 30 0 100 200 300 400 500 600 Class-Interval [P rofit per shop Fig. 3.41. Histogram showing monthly prolits. Example 37.Draw the histogram for the following data: Marks 0- 10 10 20 20 30 30 40 40 50 50 60 60 -70 S0 40 No. of Students Solution. We represent the class limits along x-axis and frequencies along y-axis. Taking class intervals as bases and the corresponding frequencies (No. of students) as heights, we construct the rectangles to get the histogram of the given frequency distribution as shown in Fig. 3.42. 20 30 70 0 40 Scale: Along x-axis 1 cm = 10 marks Along y-a xis: 1 cm = 10 studenis A 10 20 30 40 50 60 70 Marks- Flg.3.42. Histogram showing marks oblained by sludents. TYPE II. HISTOGRAM WHEN CLASS INTERVALS ARE GIVEN N EXCLUSI FORM, i.e., WHEN CLASS INTERVALS ARE NOT CONTINUOUS In a histogram, it is necessary that the adjacent rectangles be attached to each other. If w to represent the given data (in cxCusivefomm) as such we shall get a bar diagram as there w gaps in between the classes. But in a histogram the bars are continuous without any Be
  • 10. The histogram of the given data is given by Fig. 3.49. Note: The crank mark or kink ( ) in the curve on the hornzontal axis means tha lack of space this small distance representss to S. owing he anu Example 45. Draw the histogram of the following frequenc)y distribulion and show th TYPETV HISTOGRAM WITH UNEQUAL CLASS INTERVALS On your graph which represents the total number of wage-eamers in he age-group 19-n 35- 14 15 16- 17 18-20 21-24 25 29 30-34 0 00 Age group 150 i10 I10 No. of wage-earners 120 140 Solution. Here the class intervals have been marked by class-limits. As a result, the uperli of one class does not coincide with the lower limit of the next class. In order to draw a histogm the upper limit of one class must coincide with the lower limit of the next class. To draw a histogm n suchcase where the upper limit of one class does not coincide with the lower limit ofthene class, class limits of all the classes should be extended to their class-boundaries. This ill elt drawing ofa histogram from a frequency distribution in which class intervals are marked byclas limits. In this example, the classes are not of equal width. Some have less width and some have more width. So the histogram should be drawn on the basis of frequency density and not on te basis of frequency. Calculation of Histogram Class-boundary Class-width Frequency densiy Frequency (No. of wage-earners) Class-interval Age group) 13.5 15.5 15.5 17.5 17.5 20.5 (Age groupP) 14 15 120 0 16- 17 140 70 18- 20 150 0 21 24 20.5 24.5 10 27.5 25 -29 24.5 29.5 110 2 34 29.5 34.5 100 20 35 3 39 34.5 39.5 0 18 13.5 15.5 17.5 19 20.5 24.5 29.5 32 34.5 39.5 Class-boundary (Age In years Flg.3.50. Histogram showing the number of wage-eatners. The total number of wage earnerS in the age group 19 -32 is shown by the sn in the histogram. aded area
  • 11. DiagraInmiatiC 1ieprescntation 211 Example 9.7. Construct a Histogram tron the followino talla. Weight (in lbs) No. of Men 95-105 105 105-115 210 115-125 125-135 300 175 135-145 255
  • 12. Example 9.8. Draw a Histogram of the followingdata: Height in cm No. of Persons 120-129 15 130-139 20 140-154 45 155-159 25 160-179 30
  • 13. C o m p r e n E T o m 3.50 Example 42. The following table presents the number ofiterate females in the age pro (10 34) in a town: group 25-29 30-34 20-24 Age group 10-14 15-19 580 290 800 No. ofFemales : 300 980 Draw a histogram to represent the above data. discontinuous distribution. In order to draw a histogram autian. Thedifferenco
  • 14. Diagrammatic and Graphic Presentation of Data 3.15 Example 14: The following figures relate to the costof construction of a huuse in Delhi: Ttem :Cement Steel Bricks Timber Labour Miscellaneous Expenditure 20% 18% 10% 15% 25% 12% Represent the data by a suitablediagram.
  • 15. 3.14 he Example 13: Draw a pie diagram to represeni ihefollowing data ofinvestmment patterm in the Five Year Plan: 14% Agricuiture andCommunity Development 16% Irrigaiion and Power Small and Organised Industries and Minerals Transport and Communication Social senvices 29% 17% 16% 8 9 Inventories
  • 16. Example 15: Draw a suitable diagramforthe following: Expenditure on item Percentage of Total expenditure Food 65 Clothing 10 Housing 12 Fuel andlighting 5 Miscellaneous 8