SlideShare a Scribd company logo
1 of 26
Statistics is the study of the collection,
organization, analysis, interpretation, and
presentation of data. It deals with all aspects of this,
including the planning of data collection in terms of
the design of surveys and experiments.
A statistician is someone who is particularly
well versed in the ways of thinking necessary for
the successful application of statistical analysis.
Such people have often gained this experience
through working in any of a wide number of fields.
There is also a discipline called mathematical
statistics that studies statistics mathematically.
The mean is the average of the numbers: a calculated
"central" value of a set of numbers.
There are three methods to calculate out mean and these
are:-
Example:-
A class teacher has the following absentee
record of 40 students of a class for the whole
term. Find the mean number of days a student
was absent.
Number of
days
0 βˆ’ 6 6 βˆ’ 10 10 βˆ’ 14 14 βˆ’ 20 20 βˆ’ 28 28 βˆ’
38
38 βˆ’ 40
Number of
students
11 10 7 4 4 3 1
To find the class mark of each interval, the following
relation is used.
Taking 17 as assumed mean (a), di and fidi are calculated as
follows.
Solution:-
Number of days Number of
students fi
xi di = xi βˆ’ 17 fidi
0 βˆ’ 6 11 3 βˆ’ 14 βˆ’ 154
6 βˆ’ 10 10 8 βˆ’ 9 βˆ’ 90
10 βˆ’ 14 7 12 βˆ’ 5 βˆ’ 35
14 βˆ’ 20 4 17 0 0
20 βˆ’ 28 4 24 7 28
28 βˆ’ 38 3 33 16 48
38 βˆ’ 40 1 39 22 22
Total 40 βˆ’ 181
From the table, we obtain
Therefore, the mean number of days is 12.48 days for which a
student was absent.
LIMITATION:- Disadvantage of themean:Themajor disadvantage,
which doesnot always occur, isthe fact that a mean can be
dramatically affected byoutliers in theset.Forexample, if we find
the mean of the set of numbers 1, 2, 3, 4, 5 we get 3.
However, when we dramatically alter one number in thesetand
find the average again, the mean isquite different. Forexample 1,
2, 3, 4, 20 has a mean of 6.
Uses:- the mean to describe the middle of a set of data that
does not have an outlier.
The "mode" is the value that occurs most
often. If no number is repeated, then thereis
no mode for thelist.
Limitation:-Could be very far from the actual
middle of the data. The least reliable way to find the
middle or average of the data.
Uses:- the mode when the data is non-numeric or
when asked to choose the most popular item.
Example:-
The given distribution shows the number of runs
scored by some top batsmen of the world in one-
day international cricket matches.
Find the mode of the data.
Runs scored Number of batsmen
3000 βˆ’ 4000 4
4000 βˆ’ 5000 18
5000 βˆ’ 6000 9
6000 βˆ’ 7000 7
7000 βˆ’ 8000 6
8000 βˆ’ 9000 3
9000 βˆ’ 10000 1
10000 βˆ’ 11000 1
Solution:-
From the given data, it can be observed that the maximum
class frequency is 18, belonging to class interval 4000 βˆ’
5000.
Therefore, modal class = 4000 βˆ’ 5000
Lower limit (l) of modal class = 4000
Frequency (f1) of modal class = 18
Frequency (f0) of class preceding modal class = 4
Frequency (f2) of class succeeding modal class = 9
Class size (h) = 1000
Therefore, mode of the given data is 4608.7 run
The "median" is the "middle"
value in the list of numbers. To
find the median, your numbers
have to be listed in numerical
order, so you may have to
rewrite your list first.
LIMITATION: If the gap between some numbers is large,
while it is small between other numbers in the data, this can
cause the median to be a very inaccurate way to find the
middle of a set of values.
Uses:- the median to describe the middle of a set of data
that does have an outlier.
Example:-
A life insurance agent found the following data for distribution
of ages of 100 policy holders. Calculate the median age, if
policies are given only to persons having age 18 years
onwards but less than 60 year.
Age (in years) Number of policy holders
Below 20 2
Below 25 6
Below 30 24
Below 35 45
Below 40 78
Below 45 89
Below 50 92
Below 55 98
Below 60 100
Solution:-
Here, class width is not the same. There is no requirement of
adjusting the frequencies according to class intervals. The given
frequency table is of less than type represented with upper class
limits. The policies were given only to persons with age 18 years
onwards but less than 60 years. Therefore, class intervals with
their respective cumulative frequency can be defined as below.
Age (in years)
Number of policy
holders (fi)
Cumulative
frequency (cf)
18 βˆ’ 20 2 2
20 βˆ’ 25 6 βˆ’ 2 = 4 6
25 βˆ’ 30 24 βˆ’ 6 = 18 24
30 βˆ’ 35 45 βˆ’ 24 = 21 45
35 βˆ’ 40 78 βˆ’ 45 = 33 78
40 βˆ’ 45 89 βˆ’ 78 = 11 89
45 βˆ’ 50 92 βˆ’ 89 = 3 92
50 βˆ’ 55 98 βˆ’ 92 = 6 98
55 βˆ’ 60 100 βˆ’ 98 = 2 100
Total (n)
From the table, it can be observed that n = 100.
Cumulative frequency (cf) just greater than is 78, belonging to
interval 35 βˆ’ 40.
Therefore, median class = 35 βˆ’ 40
Lower limit (l) of median class = 35
Class size (h) = 5
Frequency (f) of median class = 33
Cumulative frequency (cf) of class preceding median class = 45
Therefore, median age is 35.76 years.
Also known as an ogive, this is
a curve drawn by plotting
the value of the first class on
a graph. The next plot is the
sum of the first and second
values, the third plot is the
sum of the first, second, and
third values, and so on.
Example:-
During the medical check-up of 35 students of a class, their
weights were recorded as follows:
Weight (in kg) Number of students
Less than 38 0
Less than 40 3
Less than 42 5
Less than 44 9
Less than 46 14
Less than 48 28
Less than 50 32
Less than 52 35
Draw a less than type ogive for the given data. Hence obtain the
median weight from the graph verify the result by using the
formula.
Weight (in kg)
upper class limits
Number of students
(cumulative frequency)
Less than 38 0
Less than 40 3
Less than 42 5
Less than 44 9
Less than 46 14
Less than 48 28
Less than 50 32
Less than 52 35
Solution:-
The given cumulative frequency distributions of less than type are
Taking upper class limits on x-axis and their respective cumulative
frequencies on y-axis, its ogive can be drawn as follows.
Here, n = 35
So, = 17.5
Mark the point A whose ordinate is 17.5 and its x-coordinate is
46.5. Therefore, median of this data is 46.5.
It can be observed that the difference between two consecutive
upper class limits is 2. The class marks with their respective
frequencies are obtained as below.
Weight (in kg) Frequency (f) Cumulative
frequency
Less than 38 0 0
38 βˆ’ 40 3 βˆ’ 0 = 3 3
40 βˆ’ 42 5 βˆ’ 3 = 2 5
42 βˆ’ 44 9 βˆ’ 5 = 4 9
44 βˆ’ 46 14 βˆ’ 9 = 5 14
46 βˆ’ 48 28 βˆ’ 14 = 14 28
48 βˆ’ 50 32 βˆ’ 28 = 4 32
50 βˆ’ 52 35 βˆ’ 32 = 3 35
Total (n) 35
The cumulative frequency just greater than is 28,
belonging to class interval 46 βˆ’ 48.
Median class = 46 βˆ’ 48
Lower class limit (l) of median class = 46
Frequency (f) of median class = 14
Cumulative frequency (cf) of class preceding median class = 14
Class size (h) = 2
Therefore, median of this data is 46.5.
Hence, the value of median is verified.
1. The mean for grouped data can be found by :
(i) the direct method :
(ii) the assumed mean method :
(iii) the step deviation method :
with the assumption that the frequency of a class is centered at
its mid-point, called its class mark.
2. The mode for grouped data can be found by using the formula:
where symbols have their usual meanings.
3. The cumulative frequency of a class is the frequency
obtained by adding the frequencies of all the classes
preceding the given class.
4. The median for grouped data is formed by using the
formula:
where symbols have their usual meanings.
5. Representing a cumulative frequency distribution as a
cumulative frequency curve, or an ogive of the less than
type and of the more than type.
6. The median of grouped data can be obtained graphically
as the x-coordinate of the point of intersection of the
two ogive for this data.
Maths statistcs class 10

More Related Content

What's hot

Statistics Based On Ncert X Class
Statistics Based On Ncert X ClassStatistics Based On Ncert X Class
Statistics Based On Ncert X ClassRanveer Kumar
Β 
polynomials of class 10th
polynomials of class 10thpolynomials of class 10th
polynomials of class 10thAshish Pradhan
Β 
CLASS X MATHS Polynomials
CLASS X MATHS  PolynomialsCLASS X MATHS  Polynomials
CLASS X MATHS PolynomialsRc Os
Β 
Shubhanshu math project work , polynomial
Shubhanshu math project work ,  polynomialShubhanshu math project work ,  polynomial
Shubhanshu math project work , polynomialShubhanshu Bhargava
Β 
Arithmetic progression
Arithmetic progressionArithmetic progression
Arithmetic progressionChhavi Bansal
Β 
Class IX Heron's Formula
Class IX Heron's FormulaClass IX Heron's Formula
Class IX Heron's FormulaBhawna Khurana
Β 
Statistics for Class 10 CBSE - Mathematics
Statistics for Class 10 CBSE - MathematicsStatistics for Class 10 CBSE - Mathematics
Statistics for Class 10 CBSE - MathematicsLet's Tute
Β 
Polynomials CLASS 10
Polynomials CLASS 10Polynomials CLASS 10
Polynomials CLASS 10Nihas Nichu
Β 
surface area and volume ppt for class 10
surface area and volume ppt for class 10surface area and volume ppt for class 10
surface area and volume ppt for class 107232
Β 
factorisation maths PPT by kanishk schdeva class 8th
factorisation maths PPT by kanishk schdeva class 8th factorisation maths PPT by kanishk schdeva class 8th
factorisation maths PPT by kanishk schdeva class 8th kanishk sachdeva
Β 
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10Shivam Parmar
Β 
SURFACE AREA AND VOLUME
SURFACE AREA AND VOLUMESURFACE AREA AND VOLUME
SURFACE AREA AND VOLUMEShivam Mittal
Β 
class 10 chapter 1- real numbers
class 10 chapter 1- real numbersclass 10 chapter 1- real numbers
class 10 chapter 1- real numberskaran saini
Β 
Class 9th chapter 2 maths polynomials
Class 9th chapter 2 maths polynomialsClass 9th chapter 2 maths polynomials
Class 9th chapter 2 maths polynomialsSiddharth Jain
Β 
PPT ON TRIANGLES FOR CLASS X
PPT ON TRIANGLES FOR CLASS XPPT ON TRIANGLES FOR CLASS X
PPT ON TRIANGLES FOR CLASS XMiku09
Β 
Probability 10th class
Probability 10th classProbability 10th class
Probability 10th classmanjunathindira
Β 
Class IX-Statistics.pptx
Class IX-Statistics.pptxClass IX-Statistics.pptx
Class IX-Statistics.pptxnoblesodhi
Β 

What's hot (20)

Statistics Based On Ncert X Class
Statistics Based On Ncert X ClassStatistics Based On Ncert X Class
Statistics Based On Ncert X Class
Β 
polynomials of class 10th
polynomials of class 10thpolynomials of class 10th
polynomials of class 10th
Β 
CLASS X MATHS Polynomials
CLASS X MATHS  PolynomialsCLASS X MATHS  Polynomials
CLASS X MATHS Polynomials
Β 
Shubhanshu math project work , polynomial
Shubhanshu math project work ,  polynomialShubhanshu math project work ,  polynomial
Shubhanshu math project work , polynomial
Β 
Arithmetic progression
Arithmetic progressionArithmetic progression
Arithmetic progression
Β 
Polynomials
PolynomialsPolynomials
Polynomials
Β 
Class IX Heron's Formula
Class IX Heron's FormulaClass IX Heron's Formula
Class IX Heron's Formula
Β 
Statistics for Class 10 CBSE - Mathematics
Statistics for Class 10 CBSE - MathematicsStatistics for Class 10 CBSE - Mathematics
Statistics for Class 10 CBSE - Mathematics
Β 
Polynomials CLASS 10
Polynomials CLASS 10Polynomials CLASS 10
Polynomials CLASS 10
Β 
surface area and volume ppt for class 10
surface area and volume ppt for class 10surface area and volume ppt for class 10
surface area and volume ppt for class 10
Β 
factorisation maths PPT by kanishk schdeva class 8th
factorisation maths PPT by kanishk schdeva class 8th factorisation maths PPT by kanishk schdeva class 8th
factorisation maths PPT by kanishk schdeva class 8th
Β 
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10
Chapter - 16, Sustainable Management of Natural Resources, Science, Class 10
Β 
SURFACE AREA AND VOLUME
SURFACE AREA AND VOLUMESURFACE AREA AND VOLUME
SURFACE AREA AND VOLUME
Β 
Polynomials
PolynomialsPolynomials
Polynomials
Β 
class 10 chapter 1- real numbers
class 10 chapter 1- real numbersclass 10 chapter 1- real numbers
class 10 chapter 1- real numbers
Β 
Class 9th chapter 2 maths polynomials
Class 9th chapter 2 maths polynomialsClass 9th chapter 2 maths polynomials
Class 9th chapter 2 maths polynomials
Β 
PPT ON TRIANGLES FOR CLASS X
PPT ON TRIANGLES FOR CLASS XPPT ON TRIANGLES FOR CLASS X
PPT ON TRIANGLES FOR CLASS X
Β 
Circles class 9
Circles class 9Circles class 9
Circles class 9
Β 
Probability 10th class
Probability 10th classProbability 10th class
Probability 10th class
Β 
Class IX-Statistics.pptx
Class IX-Statistics.pptxClass IX-Statistics.pptx
Class IX-Statistics.pptx
Β 

Similar to Maths statistcs class 10

Stastistics
StastisticsStastistics
StastisticsRivan001
Β 
Analysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAnalysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAeonneFlux
Β 
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptx
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptxMEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptx
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptxJhayMarkMaltoLacsam
Β 
Nota Bab 1 JF608
Nota Bab 1 JF608Nota Bab 1 JF608
Nota Bab 1 JF608Mira Awang
Β 
STATISTICS AND PROBABILITY.pptx
STATISTICS AND PROBABILITY.pptxSTATISTICS AND PROBABILITY.pptx
STATISTICS AND PROBABILITY.pptxBharathiar University
Β 
MEDIAN.pptx
MEDIAN.pptxMEDIAN.pptx
MEDIAN.pptxSreeLatha98
Β 
Utilization-of-assessment-data-assessmentinLearning1.pptx
Utilization-of-assessment-data-assessmentinLearning1.pptxUtilization-of-assessment-data-assessmentinLearning1.pptx
Utilization-of-assessment-data-assessmentinLearning1.pptxEdeleneGetes
Β 
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
Group 3  measures of central tendency and variation - (mean, median, mode, ra...Group 3  measures of central tendency and variation - (mean, median, mode, ra...
Group 3 measures of central tendency and variation - (mean, median, mode, ra...reymartyvette_0611
Β 
I. central tendency
I. central tendencyI. central tendency
I. central tendencyMaryFlorCaalim
Β 
Measures of Central Tendancy
Measures of Central TendancyMeasures of Central Tendancy
Measures of Central TendancyMARIAPPANM4
Β 
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.ppt
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.pptmeasuresofcentraltendencymeanmedianmode-140706130428-phpapp01.ppt
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.pptSoujanyaLk1
Β 
Tabulation of Data, Frequency Distribution, Contingency table
Tabulation of Data, Frequency Distribution, Contingency tableTabulation of Data, Frequency Distribution, Contingency table
Tabulation of Data, Frequency Distribution, Contingency tableJagdish Powar
Β 
Frequency distribution, central tendency, measures of dispersion
Frequency distribution, central tendency, measures of dispersionFrequency distribution, central tendency, measures of dispersion
Frequency distribution, central tendency, measures of dispersionDhwani Shah
Β 
Biostatistics Measures of central tendency
Biostatistics Measures of central tendency Biostatistics Measures of central tendency
Biostatistics Measures of central tendency HARINATHA REDDY ASWARTHA
Β 
measures of centraltendency.ppt
measures of centraltendency.pptmeasures of centraltendency.ppt
measures of centraltendency.pptSoujanyaLk1
Β 
Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Jan Nah
Β 

Similar to Maths statistcs class 10 (20)

Stastistics
StastisticsStastistics
Stastistics
Β 
Statistics
StatisticsStatistics
Statistics
Β 
Analysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAnalysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptx
Β 
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptx
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptxMEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptx
MEASURES-OF-CENTRAL-TENDENCY-lecture-edited.pptx
Β 
Nota Bab 1 JF608
Nota Bab 1 JF608Nota Bab 1 JF608
Nota Bab 1 JF608
Β 
STATISTICS AND PROBABILITY.pptx
STATISTICS AND PROBABILITY.pptxSTATISTICS AND PROBABILITY.pptx
STATISTICS AND PROBABILITY.pptx
Β 
MEDIAN.pptx
MEDIAN.pptxMEDIAN.pptx
MEDIAN.pptx
Β 
Utilization-of-assessment-data-assessmentinLearning1.pptx
Utilization-of-assessment-data-assessmentinLearning1.pptxUtilization-of-assessment-data-assessmentinLearning1.pptx
Utilization-of-assessment-data-assessmentinLearning1.pptx
Β 
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
Group 3  measures of central tendency and variation - (mean, median, mode, ra...Group 3  measures of central tendency and variation - (mean, median, mode, ra...
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
Β 
I. central tendency
I. central tendencyI. central tendency
I. central tendency
Β 
Measures of Central Tendancy
Measures of Central TendancyMeasures of Central Tendancy
Measures of Central Tendancy
Β 
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.ppt
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.pptmeasuresofcentraltendencymeanmedianmode-140706130428-phpapp01.ppt
measuresofcentraltendencymeanmedianmode-140706130428-phpapp01.ppt
Β 
Tabulation of Data, Frequency Distribution, Contingency table
Tabulation of Data, Frequency Distribution, Contingency tableTabulation of Data, Frequency Distribution, Contingency table
Tabulation of Data, Frequency Distribution, Contingency table
Β 
Frequency distribution, central tendency, measures of dispersion
Frequency distribution, central tendency, measures of dispersionFrequency distribution, central tendency, measures of dispersion
Frequency distribution, central tendency, measures of dispersion
Β 
Biostatistics Measures of central tendency
Biostatistics Measures of central tendency Biostatistics Measures of central tendency
Biostatistics Measures of central tendency
Β 
Mod mean quartile
Mod mean quartileMod mean quartile
Mod mean quartile
Β 
measures of centraltendency.ppt
measures of centraltendency.pptmeasures of centraltendency.ppt
measures of centraltendency.ppt
Β 
Basic statics
Basic staticsBasic statics
Basic statics
Β 
Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency
Β 
Central tendency m,m,m 1.2
Central tendency m,m,m 1.2Central tendency m,m,m 1.2
Central tendency m,m,m 1.2
Β 

More from Rc Os

Dove
DoveDove
DoveRc Os
Β 
CLASS IV ENGLISH
CLASS IV ENGLISHCLASS IV ENGLISH
CLASS IV ENGLISHRc Os
Β 
CLASS 4 MATHS
CLASS 4 MATHSCLASS 4 MATHS
CLASS 4 MATHSRc Os
Β 
CLASS 4 MATHS
CLASS 4 MATHSCLASS 4 MATHS
CLASS 4 MATHSRc Os
Β 
CLASS III MATHS
CLASS III MATHS CLASS III MATHS
CLASS III MATHS Rc Os
Β 
CLASS III MATHS
CLASS III MATHSCLASS III MATHS
CLASS III MATHSRc Os
Β 
Changing times.
Changing times.Changing times.
Changing times.Rc Os
Β 
3 class english
3 class english3 class english
3 class englishRc Os
Β 
Clss ii english-the mouse---
Clss ii  english-the mouse---Clss ii  english-the mouse---
Clss ii english-the mouse---Rc Os
Β 
Rainbow
RainbowRainbow
RainbowRc Os
Β 
NUMBERS 1 TO 20
NUMBERS 1 TO 20NUMBERS 1 TO 20
NUMBERS 1 TO 20Rc Os
Β 
TIME
TIMETIME
TIMERc Os
Β 
MEASUREMENTS
MEASUREMENTSMEASUREMENTS
MEASUREMENTSRc Os
Β 
DATA HANDLING
DATA HANDLINGDATA HANDLING
DATA HANDLINGRc Os
Β 
patterns
 patterns patterns
patternsRc Os
Β 
Who is heavier
Who is heavierWho is heavier
Who is heavierRc Os
Β 
Sundari
SundariSundari
SundariRc Os
Β 
The tiger and the mosquitoe
The tiger and the mosquitoeThe tiger and the mosquitoe
The tiger and the mosquitoeRc Os
Β 
Photoshop
PhotoshopPhotoshop
PhotoshopRc Os
Β 
COMPUTERS Database
COMPUTERS Database COMPUTERS Database
COMPUTERS Database Rc Os
Β 

More from Rc Os (20)

Dove
DoveDove
Dove
Β 
CLASS IV ENGLISH
CLASS IV ENGLISHCLASS IV ENGLISH
CLASS IV ENGLISH
Β 
CLASS 4 MATHS
CLASS 4 MATHSCLASS 4 MATHS
CLASS 4 MATHS
Β 
CLASS 4 MATHS
CLASS 4 MATHSCLASS 4 MATHS
CLASS 4 MATHS
Β 
CLASS III MATHS
CLASS III MATHS CLASS III MATHS
CLASS III MATHS
Β 
CLASS III MATHS
CLASS III MATHSCLASS III MATHS
CLASS III MATHS
Β 
Changing times.
Changing times.Changing times.
Changing times.
Β 
3 class english
3 class english3 class english
3 class english
Β 
Clss ii english-the mouse---
Clss ii  english-the mouse---Clss ii  english-the mouse---
Clss ii english-the mouse---
Β 
Rainbow
RainbowRainbow
Rainbow
Β 
NUMBERS 1 TO 20
NUMBERS 1 TO 20NUMBERS 1 TO 20
NUMBERS 1 TO 20
Β 
TIME
TIMETIME
TIME
Β 
MEASUREMENTS
MEASUREMENTSMEASUREMENTS
MEASUREMENTS
Β 
DATA HANDLING
DATA HANDLINGDATA HANDLING
DATA HANDLING
Β 
patterns
 patterns patterns
patterns
Β 
Who is heavier
Who is heavierWho is heavier
Who is heavier
Β 
Sundari
SundariSundari
Sundari
Β 
The tiger and the mosquitoe
The tiger and the mosquitoeThe tiger and the mosquitoe
The tiger and the mosquitoe
Β 
Photoshop
PhotoshopPhotoshop
Photoshop
Β 
COMPUTERS Database
COMPUTERS Database COMPUTERS Database
COMPUTERS Database
Β 

Recently uploaded

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
Β 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
Β 
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
Β 
PSYCHIATRIC History collection FORMAT.pptx
PSYCHIATRIC   History collection FORMAT.pptxPSYCHIATRIC   History collection FORMAT.pptx
PSYCHIATRIC History collection FORMAT.pptxPoojaSen20
Β 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
Β 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppCeline George
Β 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
Β 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
Β 
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
Β 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
Β 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
Β 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docxPoojaSen20
Β 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
Β 
Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsKarinaGenton
Β 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
Β 
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
Β 
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
Β 

Recently uploaded (20)

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
Β 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
Β 
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
Β 
PSYCHIATRIC History collection FORMAT.pptx
PSYCHIATRIC   History collection FORMAT.pptxPSYCHIATRIC   History collection FORMAT.pptx
PSYCHIATRIC History collection FORMAT.pptx
Β 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
Β 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website App
Β 
Model Call Girl in Tilak Nagar Delhi reach out to us at πŸ”9953056974πŸ”
Model Call Girl in Tilak Nagar Delhi reach out to us at πŸ”9953056974πŸ”Model Call Girl in Tilak Nagar Delhi reach out to us at πŸ”9953056974πŸ”
Model Call Girl in Tilak Nagar Delhi reach out to us at πŸ”9953056974πŸ”
Β 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
Β 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
Β 
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
Β 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
Β 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
Β 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docx
Β 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
Β 
Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its Characteristics
Β 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
Β 
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
β€œOh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
Β 
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
Β 
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
Β 
CΓ³digo Creativo y Arte de Software | Unidad 1
CΓ³digo Creativo y Arte de Software | Unidad 1CΓ³digo Creativo y Arte de Software | Unidad 1
CΓ³digo Creativo y Arte de Software | Unidad 1
Β 

Maths statistcs class 10

  • 1.
  • 2. Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments. A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields. There is also a discipline called mathematical statistics that studies statistics mathematically.
  • 3. The mean is the average of the numbers: a calculated "central" value of a set of numbers. There are three methods to calculate out mean and these are:-
  • 4. Example:- A class teacher has the following absentee record of 40 students of a class for the whole term. Find the mean number of days a student was absent. Number of days 0 βˆ’ 6 6 βˆ’ 10 10 βˆ’ 14 14 βˆ’ 20 20 βˆ’ 28 28 βˆ’ 38 38 βˆ’ 40 Number of students 11 10 7 4 4 3 1
  • 5. To find the class mark of each interval, the following relation is used. Taking 17 as assumed mean (a), di and fidi are calculated as follows. Solution:- Number of days Number of students fi xi di = xi βˆ’ 17 fidi 0 βˆ’ 6 11 3 βˆ’ 14 βˆ’ 154 6 βˆ’ 10 10 8 βˆ’ 9 βˆ’ 90 10 βˆ’ 14 7 12 βˆ’ 5 βˆ’ 35 14 βˆ’ 20 4 17 0 0 20 βˆ’ 28 4 24 7 28 28 βˆ’ 38 3 33 16 48 38 βˆ’ 40 1 39 22 22 Total 40 βˆ’ 181
  • 6. From the table, we obtain Therefore, the mean number of days is 12.48 days for which a student was absent.
  • 7. LIMITATION:- Disadvantage of themean:Themajor disadvantage, which doesnot always occur, isthe fact that a mean can be dramatically affected byoutliers in theset.Forexample, if we find the mean of the set of numbers 1, 2, 3, 4, 5 we get 3. However, when we dramatically alter one number in thesetand find the average again, the mean isquite different. Forexample 1, 2, 3, 4, 20 has a mean of 6. Uses:- the mean to describe the middle of a set of data that does not have an outlier.
  • 8. The "mode" is the value that occurs most often. If no number is repeated, then thereis no mode for thelist.
  • 9. Limitation:-Could be very far from the actual middle of the data. The least reliable way to find the middle or average of the data. Uses:- the mode when the data is non-numeric or when asked to choose the most popular item.
  • 10. Example:- The given distribution shows the number of runs scored by some top batsmen of the world in one- day international cricket matches. Find the mode of the data. Runs scored Number of batsmen 3000 βˆ’ 4000 4 4000 βˆ’ 5000 18 5000 βˆ’ 6000 9 6000 βˆ’ 7000 7 7000 βˆ’ 8000 6 8000 βˆ’ 9000 3 9000 βˆ’ 10000 1 10000 βˆ’ 11000 1
  • 11. Solution:- From the given data, it can be observed that the maximum class frequency is 18, belonging to class interval 4000 βˆ’ 5000. Therefore, modal class = 4000 βˆ’ 5000 Lower limit (l) of modal class = 4000 Frequency (f1) of modal class = 18 Frequency (f0) of class preceding modal class = 4 Frequency (f2) of class succeeding modal class = 9 Class size (h) = 1000 Therefore, mode of the given data is 4608.7 run
  • 12. The "median" is the "middle" value in the list of numbers. To find the median, your numbers have to be listed in numerical order, so you may have to rewrite your list first.
  • 13. LIMITATION: If the gap between some numbers is large, while it is small between other numbers in the data, this can cause the median to be a very inaccurate way to find the middle of a set of values. Uses:- the median to describe the middle of a set of data that does have an outlier.
  • 14. Example:- A life insurance agent found the following data for distribution of ages of 100 policy holders. Calculate the median age, if policies are given only to persons having age 18 years onwards but less than 60 year. Age (in years) Number of policy holders Below 20 2 Below 25 6 Below 30 24 Below 35 45 Below 40 78 Below 45 89 Below 50 92 Below 55 98 Below 60 100
  • 15. Solution:- Here, class width is not the same. There is no requirement of adjusting the frequencies according to class intervals. The given frequency table is of less than type represented with upper class limits. The policies were given only to persons with age 18 years onwards but less than 60 years. Therefore, class intervals with their respective cumulative frequency can be defined as below. Age (in years) Number of policy holders (fi) Cumulative frequency (cf) 18 βˆ’ 20 2 2 20 βˆ’ 25 6 βˆ’ 2 = 4 6 25 βˆ’ 30 24 βˆ’ 6 = 18 24 30 βˆ’ 35 45 βˆ’ 24 = 21 45 35 βˆ’ 40 78 βˆ’ 45 = 33 78 40 βˆ’ 45 89 βˆ’ 78 = 11 89 45 βˆ’ 50 92 βˆ’ 89 = 3 92 50 βˆ’ 55 98 βˆ’ 92 = 6 98 55 βˆ’ 60 100 βˆ’ 98 = 2 100 Total (n)
  • 16. From the table, it can be observed that n = 100. Cumulative frequency (cf) just greater than is 78, belonging to interval 35 βˆ’ 40. Therefore, median class = 35 βˆ’ 40 Lower limit (l) of median class = 35 Class size (h) = 5 Frequency (f) of median class = 33 Cumulative frequency (cf) of class preceding median class = 45 Therefore, median age is 35.76 years.
  • 17. Also known as an ogive, this is a curve drawn by plotting the value of the first class on a graph. The next plot is the sum of the first and second values, the third plot is the sum of the first, second, and third values, and so on.
  • 18. Example:- During the medical check-up of 35 students of a class, their weights were recorded as follows: Weight (in kg) Number of students Less than 38 0 Less than 40 3 Less than 42 5 Less than 44 9 Less than 46 14 Less than 48 28 Less than 50 32 Less than 52 35 Draw a less than type ogive for the given data. Hence obtain the median weight from the graph verify the result by using the formula.
  • 19. Weight (in kg) upper class limits Number of students (cumulative frequency) Less than 38 0 Less than 40 3 Less than 42 5 Less than 44 9 Less than 46 14 Less than 48 28 Less than 50 32 Less than 52 35 Solution:- The given cumulative frequency distributions of less than type are Taking upper class limits on x-axis and their respective cumulative frequencies on y-axis, its ogive can be drawn as follows.
  • 20. Here, n = 35 So, = 17.5 Mark the point A whose ordinate is 17.5 and its x-coordinate is 46.5. Therefore, median of this data is 46.5.
  • 21. It can be observed that the difference between two consecutive upper class limits is 2. The class marks with their respective frequencies are obtained as below.
  • 22. Weight (in kg) Frequency (f) Cumulative frequency Less than 38 0 0 38 βˆ’ 40 3 βˆ’ 0 = 3 3 40 βˆ’ 42 5 βˆ’ 3 = 2 5 42 βˆ’ 44 9 βˆ’ 5 = 4 9 44 βˆ’ 46 14 βˆ’ 9 = 5 14 46 βˆ’ 48 28 βˆ’ 14 = 14 28 48 βˆ’ 50 32 βˆ’ 28 = 4 32 50 βˆ’ 52 35 βˆ’ 32 = 3 35 Total (n) 35 The cumulative frequency just greater than is 28, belonging to class interval 46 βˆ’ 48. Median class = 46 βˆ’ 48 Lower class limit (l) of median class = 46
  • 23. Frequency (f) of median class = 14 Cumulative frequency (cf) of class preceding median class = 14 Class size (h) = 2 Therefore, median of this data is 46.5. Hence, the value of median is verified.
  • 24. 1. The mean for grouped data can be found by : (i) the direct method : (ii) the assumed mean method : (iii) the step deviation method : with the assumption that the frequency of a class is centered at its mid-point, called its class mark. 2. The mode for grouped data can be found by using the formula: where symbols have their usual meanings.
  • 25. 3. The cumulative frequency of a class is the frequency obtained by adding the frequencies of all the classes preceding the given class. 4. The median for grouped data is formed by using the formula: where symbols have their usual meanings. 5. Representing a cumulative frequency distribution as a cumulative frequency curve, or an ogive of the less than type and of the more than type. 6. The median of grouped data can be obtained graphically as the x-coordinate of the point of intersection of the two ogive for this data.