SlideShare a Scribd company logo
1 of 18
PROGRAMME B.COM
SUBJECT
QUANTITATIVE TECHNIQUE – I
SEMESTER III
UNIVERSITY VIJAYANAGAR SRI
KRISHNADEVARAYA UNIVERSITY,
BALLARI
SESSION 07
RECAP
• Meaning & Definition of Classification
• Objectives of Classification and Rules of Classification
LEARNING OBJECTIVES
• The aim of the chapter is to make students to
present data in textual and Tabular format including
the technique of creating frequency distribution
and working out bi-variate distribution table
LEARNING OUTCOMES
• After the Chapter, The Students Shall be able to
Describe and Understand the Rules & Types of
Classification, Frequency Distribution, Class Interval
& its Types, Basic Principles Tabulation and The
Sorting of Data.
SESSION - 7
• Types of Classifications and Types of Series (
Individual , Discrete & Continuous)
TYPES OF CLASSIFICATION
• Classification by Time or Chronological Classification
The method of classifying data according to time
component is known as classification by time or
chronological classification.
Example 3.1 source (http://www.brainkart.com/article)
CONT.,
• Classification by Space (Spatial) or Geographical
Classification.
The method of classifying data with reference to
geographical location such as countries, states, cities,
districts, etc., is called classification by space or
Geographical Classification. Example 3.3 source
(http://www.brainkart.com/article)
CONT.,
• Classification by Attributes or Qualitative classification
The method of classifying statistical data on the basis of
attribute is said to be classification by attributes or
qualitative classification. Examples of attributes include
nationality, religion, gender, marital status, literacy and so
on.Example 3.1 source (http://www.brainkart.com/article)
CONT.,
• Classification by Size or Quantitative Classification
When the characteristics are measured on numerical scale,
they may be classified on the basis of their magnitude. Such
a classification is known as classification by size or
quantitative classification. For example data relating to the
characteristics such as height, weight, age, income, marks
of students, production and consumption, etc.,
source
(http://www.brain
kart.com/article)
TYPES OF SERIES
• According to Erricker Frequency Distribution is a
classification according to the number possessing the
same value of the variables.
• Basically Frequency can be classified into two types
I. Univariate Frequency Distribution
II. Bivariate Frequency Distribution
Univariate Frequency Distribution is divide into three
categories
Individual Frequency distribution Series
Discrete or Ungrouped Frequency distribution
series
Continuous or Grouped Frequency distribution
series
CONT.,
• Individual Frequency distribution Series
These are those series where items are listed Singly after
observation, as distinguished from listing them in groups.
• Discrete or Ungrouped Frequency distribution series
In this case, the observations or variables are counted
that how many times repeated is called the frequency of
that class.
• Continuous or Grouped Frequency distribution series
The variables which can take any intermediate value
between the smallest and longest value in the
distribution
CONT.,
• Under Continuous or Grouped Frequency distribution
series certain technical terms are important to
understand they are
 Class limits (Ex; 10-20,Lower Limit 10,Upper Limit 20)
 Class interval ( Upper Limit – Lower Limit)
 Exclusive or Overlapping Method (Ex; 10-20, 20-30)
 Inclusive or Non Overlapping method (Ex; 10-19,20-29)
 Class Frequency
 Class marks or Mid Values
 Class boundaries or True class intervals
 Cumulative Frequency
SUMMARY
As we already discussed and learnt today on
Classifications and Tabulation as below
• Types of classification
• Types of Series ( Individual , Discrete & Continuous)
MCQs
1 . The method of classifying data according to time
Component is known as
a) Chronological Classification
b) Geographical Classification
c) Qualitative Classification
d) Quantitative Classification
2. Types of Classification includes
a) Chronological Classification
b) Geographical Classification
c) Qualitative Classification
d) All of the above
MCQs
3. A Frequency distribution
a) Arranges observations in an increasing order
b) Arranges observations in terms of a number of
groups
c) Relaters to a measurable feature
d) All of these
4. The frequency distribution of a continuous variable is
known as
a) Grouped Frequency distribution
b) Simple Frequency distribution
c) (a) Or (b)
d) (a) And (b)
MCQs
5. The number of observations falling within a class is called
a) Density
b) Frequency
c) Both
d) None
ANSWERS
1. A
2. D
3. D
4. A
5. B
REFERENCES
• S.P. Gupta, Sultan Chand and Sons Publications, 2017
• S. C. Gupta, Himalaya Publishing House,
Fundamentals of Statistics, 2018
• R.S.N Pillai and Bagavathi, S.Chand publications, 2010
THANK YOU

More Related Content

Similar to Tabulation and Classification

Ch 3 Organisation of Data 1 (1).pptx
Ch 3 Organisation of Data 1 (1).pptxCh 3 Organisation of Data 1 (1).pptx
Ch 3 Organisation of Data 1 (1).pptxsyedmohd9
 
Organisation of Data
Organisation of Data Organisation of Data
Organisation of Data Saji Thomas
 
Sampling and Data_Update.ppt
Sampling and Data_Update.pptSampling and Data_Update.ppt
Sampling and Data_Update.pptMdShohelRana69
 
Measures of Dispersion
Measures of DispersionMeasures of Dispersion
Measures of DispersionAkkiMaruthi2
 
BASIC CONCEPTS in STAT 1 [Autosaved].pptx
BASIC CONCEPTS in STAT 1 [Autosaved].pptxBASIC CONCEPTS in STAT 1 [Autosaved].pptx
BASIC CONCEPTS in STAT 1 [Autosaved].pptxJhunafilRas2
 
Types of table, Preparation of Blank table
Types of table, Preparation of Blank tableTypes of table, Preparation of Blank table
Types of table, Preparation of Blank tableAkkiMaruthi2
 
Classification of data ppt.pptx
Classification of data ppt.pptxClassification of data ppt.pptx
Classification of data ppt.pptxSonuChauhan61
 
Bi variate frequency distribution table 1
Bi variate frequency distribution table 1Bi variate frequency distribution table 1
Bi variate frequency distribution table 1AkkiMaruthi2
 
UNIT 3: Data Warehousing and Data Mining
UNIT 3: Data Warehousing and Data MiningUNIT 3: Data Warehousing and Data Mining
UNIT 3: Data Warehousing and Data MiningNandakumar P
 
Group-4-Report-Frequency-Distribution.ppt
Group-4-Report-Frequency-Distribution.pptGroup-4-Report-Frequency-Distribution.ppt
Group-4-Report-Frequency-Distribution.pptNectorMoradaRapsingB
 
ORGANISATION OF DATA.pptx
ORGANISATION OF DATA.pptxORGANISATION OF DATA.pptx
ORGANISATION OF DATA.pptxajesh ps
 
Processing of data in research
Processing of data in researchProcessing of data in research
Processing of data in researchHazirAli
 
Introduction to Data Analysis for Nurse Researchers
Introduction to Data Analysis for Nurse ResearchersIntroduction to Data Analysis for Nurse Researchers
Introduction to Data Analysis for Nurse ResearchersRupa Verma
 
Census & sample methods of collection of data
Census & sample methods of collection of dataCensus & sample methods of collection of data
Census & sample methods of collection of dataYashikaGupta50
 

Similar to Tabulation and Classification (20)

Ch 3 Organisation of Data 1 (1).pptx
Ch 3 Organisation of Data 1 (1).pptxCh 3 Organisation of Data 1 (1).pptx
Ch 3 Organisation of Data 1 (1).pptx
 
Organisation of Data
Organisation of Data Organisation of Data
Organisation of Data
 
Sampling and Data_Update.ppt
Sampling and Data_Update.pptSampling and Data_Update.ppt
Sampling and Data_Update.ppt
 
Measures of Dispersion
Measures of DispersionMeasures of Dispersion
Measures of Dispersion
 
Unit 1 - Statistics (Part 1).pptx
Unit 1 - Statistics (Part 1).pptxUnit 1 - Statistics (Part 1).pptx
Unit 1 - Statistics (Part 1).pptx
 
BASIC CONCEPTS in STAT 1 [Autosaved].pptx
BASIC CONCEPTS in STAT 1 [Autosaved].pptxBASIC CONCEPTS in STAT 1 [Autosaved].pptx
BASIC CONCEPTS in STAT 1 [Autosaved].pptx
 
Types of table, Preparation of Blank table
Types of table, Preparation of Blank tableTypes of table, Preparation of Blank table
Types of table, Preparation of Blank table
 
Tabulation 2
Tabulation 2Tabulation 2
Tabulation 2
 
Classification of data ppt.pptx
Classification of data ppt.pptxClassification of data ppt.pptx
Classification of data ppt.pptx
 
Bi variate frequency distribution table 1
Bi variate frequency distribution table 1Bi variate frequency distribution table 1
Bi variate frequency distribution table 1
 
Bivariate table 1
Bivariate table 1Bivariate table 1
Bivariate table 1
 
UNIT 3: Data Warehousing and Data Mining
UNIT 3: Data Warehousing and Data MiningUNIT 3: Data Warehousing and Data Mining
UNIT 3: Data Warehousing and Data Mining
 
L7PDF.pdf
L7PDF.pdfL7PDF.pdf
L7PDF.pdf
 
Group-4-Report-Frequency-Distribution.ppt
Group-4-Report-Frequency-Distribution.pptGroup-4-Report-Frequency-Distribution.ppt
Group-4-Report-Frequency-Distribution.ppt
 
7 dan 8
7 dan 87 dan 8
7 dan 8
 
ORGANISATION OF DATA.pptx
ORGANISATION OF DATA.pptxORGANISATION OF DATA.pptx
ORGANISATION OF DATA.pptx
 
Processing of data in research
Processing of data in researchProcessing of data in research
Processing of data in research
 
Introduction to Data Analysis for Nurse Researchers
Introduction to Data Analysis for Nurse ResearchersIntroduction to Data Analysis for Nurse Researchers
Introduction to Data Analysis for Nurse Researchers
 
Ch 3 DATA.doc
Ch 3 DATA.docCh 3 DATA.doc
Ch 3 DATA.doc
 
Census & sample methods of collection of data
Census & sample methods of collection of dataCensus & sample methods of collection of data
Census & sample methods of collection of data
 

More from AkkiMaruthi2

Bi variate Table 2
Bi variate Table 2Bi variate Table 2
Bi variate Table 2AkkiMaruthi2
 
Classification Theory
Classification Theory Classification Theory
Classification Theory AkkiMaruthi2
 
Frequency Distribution Table 4
Frequency Distribution Table 4Frequency Distribution Table 4
Frequency Distribution Table 4AkkiMaruthi2
 
Frequency Distribution Table 5
Frequency Distribution Table 5Frequency Distribution Table 5
Frequency Distribution Table 5AkkiMaruthi2
 
Frequency Distribution Table 2
Frequency Distribution Table 2Frequency Distribution Table 2
Frequency Distribution Table 2AkkiMaruthi2
 
Mean, median & mode 2
Mean, median & mode 2Mean, median & mode 2
Mean, median & mode 2AkkiMaruthi2
 
mean median mode 3
mean median mode 3mean median mode 3
mean median mode 3AkkiMaruthi2
 
Mean, median & mode 1
Mean, median & mode 1Mean, median & mode 1
Mean, median & mode 1AkkiMaruthi2
 
Range, Q.D and Co-efficient 2
Range, Q.D and Co-efficient 2Range, Q.D and Co-efficient 2
Range, Q.D and Co-efficient 2AkkiMaruthi2
 
graphical representation 1
graphical representation 1graphical representation 1
graphical representation 1AkkiMaruthi2
 
graphical representation 4
graphical representation 4graphical representation 4
graphical representation 4AkkiMaruthi2
 
graphical representation 5
graphical representation 5graphical representation 5
graphical representation 5AkkiMaruthi2
 
graphical representation 2
graphical representation 2graphical representation 2
graphical representation 2AkkiMaruthi2
 
Missing frequency 1
Missing frequency 1Missing frequency 1
Missing frequency 1AkkiMaruthi2
 

More from AkkiMaruthi2 (20)

Bi variate Table 2
Bi variate Table 2Bi variate Table 2
Bi variate Table 2
 
Classification Theory
Classification Theory Classification Theory
Classification Theory
 
tabulation 3
tabulation 3tabulation 3
tabulation 3
 
Blank Table 1
Blank Table 1Blank Table 1
Blank Table 1
 
Frequency Distribution Table 4
Frequency Distribution Table 4Frequency Distribution Table 4
Frequency Distribution Table 4
 
Frequency Distribution Table 5
Frequency Distribution Table 5Frequency Distribution Table 5
Frequency Distribution Table 5
 
Frequency Distribution Table 2
Frequency Distribution Table 2Frequency Distribution Table 2
Frequency Distribution Table 2
 
Mean, median & mode 2
Mean, median & mode 2Mean, median & mode 2
Mean, median & mode 2
 
KPC skewness 1
KPC skewness 1KPC skewness 1
KPC skewness 1
 
mean median mode 3
mean median mode 3mean median mode 3
mean median mode 3
 
Mean, median & mode 1
Mean, median & mode 1Mean, median & mode 1
Mean, median & mode 1
 
Range, Q.D and Co-efficient 2
Range, Q.D and Co-efficient 2Range, Q.D and Co-efficient 2
Range, Q.D and Co-efficient 2
 
graphical representation 1
graphical representation 1graphical representation 1
graphical representation 1
 
KPC skewness 2
KPC skewness 2KPC skewness 2
KPC skewness 2
 
graphical representation 4
graphical representation 4graphical representation 4
graphical representation 4
 
graphical representation 5
graphical representation 5graphical representation 5
graphical representation 5
 
graphical representation 2
graphical representation 2graphical representation 2
graphical representation 2
 
Missing frequency 1
Missing frequency 1Missing frequency 1
Missing frequency 1
 
diagrams theory
diagrams theorydiagrams theory
diagrams theory
 
KPC skewness 2
KPC skewness 2KPC skewness 2
KPC skewness 2
 

Recently uploaded

HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxEsquimalt MFRC
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxRamakrishna Reddy Bijjam
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxcallscotland1987
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.pptRamjanShidvankar
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin ClassesCeline George
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfNirmal Dwivedi
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfSherif Taha
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Association for Project Management
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...ZurliaSoop
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfAdmir Softic
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentationcamerronhm
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxVishalSingh1417
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseAnaAcapella
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSCeline George
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and ModificationsMJDuyan
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...pradhanghanshyam7136
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxAreebaZafar22
 
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxSKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxAmanpreet Kaur
 

Recently uploaded (20)

HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptx
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POS
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxSKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
 

Tabulation and Classification

  • 1. PROGRAMME B.COM SUBJECT QUANTITATIVE TECHNIQUE – I SEMESTER III UNIVERSITY VIJAYANAGAR SRI KRISHNADEVARAYA UNIVERSITY, BALLARI SESSION 07
  • 2. RECAP • Meaning & Definition of Classification • Objectives of Classification and Rules of Classification
  • 3. LEARNING OBJECTIVES • The aim of the chapter is to make students to present data in textual and Tabular format including the technique of creating frequency distribution and working out bi-variate distribution table
  • 4. LEARNING OUTCOMES • After the Chapter, The Students Shall be able to Describe and Understand the Rules & Types of Classification, Frequency Distribution, Class Interval & its Types, Basic Principles Tabulation and The Sorting of Data.
  • 5. SESSION - 7 • Types of Classifications and Types of Series ( Individual , Discrete & Continuous)
  • 6. TYPES OF CLASSIFICATION • Classification by Time or Chronological Classification The method of classifying data according to time component is known as classification by time or chronological classification. Example 3.1 source (http://www.brainkart.com/article)
  • 7. CONT., • Classification by Space (Spatial) or Geographical Classification. The method of classifying data with reference to geographical location such as countries, states, cities, districts, etc., is called classification by space or Geographical Classification. Example 3.3 source (http://www.brainkart.com/article)
  • 8. CONT., • Classification by Attributes or Qualitative classification The method of classifying statistical data on the basis of attribute is said to be classification by attributes or qualitative classification. Examples of attributes include nationality, religion, gender, marital status, literacy and so on.Example 3.1 source (http://www.brainkart.com/article)
  • 9. CONT., • Classification by Size or Quantitative Classification When the characteristics are measured on numerical scale, they may be classified on the basis of their magnitude. Such a classification is known as classification by size or quantitative classification. For example data relating to the characteristics such as height, weight, age, income, marks of students, production and consumption, etc., source (http://www.brain kart.com/article)
  • 10. TYPES OF SERIES • According to Erricker Frequency Distribution is a classification according to the number possessing the same value of the variables. • Basically Frequency can be classified into two types I. Univariate Frequency Distribution II. Bivariate Frequency Distribution Univariate Frequency Distribution is divide into three categories Individual Frequency distribution Series Discrete or Ungrouped Frequency distribution series Continuous or Grouped Frequency distribution series
  • 11. CONT., • Individual Frequency distribution Series These are those series where items are listed Singly after observation, as distinguished from listing them in groups. • Discrete or Ungrouped Frequency distribution series In this case, the observations or variables are counted that how many times repeated is called the frequency of that class. • Continuous or Grouped Frequency distribution series The variables which can take any intermediate value between the smallest and longest value in the distribution
  • 12. CONT., • Under Continuous or Grouped Frequency distribution series certain technical terms are important to understand they are  Class limits (Ex; 10-20,Lower Limit 10,Upper Limit 20)  Class interval ( Upper Limit – Lower Limit)  Exclusive or Overlapping Method (Ex; 10-20, 20-30)  Inclusive or Non Overlapping method (Ex; 10-19,20-29)  Class Frequency  Class marks or Mid Values  Class boundaries or True class intervals  Cumulative Frequency
  • 13. SUMMARY As we already discussed and learnt today on Classifications and Tabulation as below • Types of classification • Types of Series ( Individual , Discrete & Continuous)
  • 14. MCQs 1 . The method of classifying data according to time Component is known as a) Chronological Classification b) Geographical Classification c) Qualitative Classification d) Quantitative Classification 2. Types of Classification includes a) Chronological Classification b) Geographical Classification c) Qualitative Classification d) All of the above
  • 15. MCQs 3. A Frequency distribution a) Arranges observations in an increasing order b) Arranges observations in terms of a number of groups c) Relaters to a measurable feature d) All of these 4. The frequency distribution of a continuous variable is known as a) Grouped Frequency distribution b) Simple Frequency distribution c) (a) Or (b) d) (a) And (b)
  • 16. MCQs 5. The number of observations falling within a class is called a) Density b) Frequency c) Both d) None ANSWERS 1. A 2. D 3. D 4. A 5. B
  • 17. REFERENCES • S.P. Gupta, Sultan Chand and Sons Publications, 2017 • S. C. Gupta, Himalaya Publishing House, Fundamentals of Statistics, 2018 • R.S.N Pillai and Bagavathi, S.Chand publications, 2010