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MathsData Handling
Maths
Maths
  • Numbers
  • 1. Number Systems
  • Algebra
  • 2. Algebraic Expressions
  • 3. Linear Equations
  • 4. Polynomials
  • 5. Quadratic Equations
  • 6. Arithmetic Progressions
  • 7. Inequalities
  • 8. Logarithms
  • 9. Factorisation
  • Geometry
  • 10. Lines and Angles
  • 11. Triangles
  • 12. Quadrilaterals
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  • 15. Coordinate Geometry
  • Mensuration
  • 16. 2D Mensuration
  • 17. 3D Mensuration
  • Trigonometry
  • 18. Introduction to Trigonometry
  • 19. Trigonometric Identities
  • 20. Heights and Distances
  • 21. Trigonometric Functions
  • 22. Inverse Trigonometric Functions
  • Advanced Algebra
  • 23. Sequences and Series
  • 24. Matrices
  • 25. Determinants
  • 26. Complex Numbers
  • 27. Permutations and Combinations
  • 28. Binomial Theorem
  • 29. Sets
  • 30. Relations
  • 31. Functions
  • Calculus
  • 32. Limits
  • 33. Continuity
  • 34. Differentiation
  • 35. Applications of Derivatives
  • 36. Integration
  • 37. Applications of Integrals
  • 38. Differential Equations
  • Vectors and 3D Geometry
  • 39. Vectors
  • Statistics and Probability
  • 40. Data Handling
    • 40.1. Introduction to Data
    • 40.2. Primary and Secondary Data
    • 40.3. Tabular Presentation of Data
    • 40.4. Graphical Representation (Bar Graphs, Histograms, Pie Charts)
    • 40.5. Frequency Distribution Tables
    • 40.6. Grouped and Ungrouped Data
  • 41. Measures of Central Tendency
  • 42. Measures of Dispersion
  • 43. Correlation
  • 44. Probability
  • 45. Random Variables
  • 46. Probability Distributions
  • Linear Programming
  • 47. Formulation of Linear Programming Problems
  • 48. Graphical Method
  • 49. Linear Programming - Constraints and Feasible Region
  • 50. Optimization Problems
  • Mathematical Reasoning
  • 51. Statements
  • 52. Logical Connectives
  • 53. Implications
  • 54. Validity of Statements and Arguments
  • Numbers
  • 1. Number Systems
  • Algebra
  • 2. Algebraic Expressions
  • 3. Linear Equations
  • 4. Polynomials
  • 5. Quadratic Equations
  • 6. Arithmetic Progressions
  • 7. Inequalities
  • 8. Logarithms
  • 9. Factorisation
  • Geometry
  • 10. Lines and Angles
  • 11. Triangles
  • 12. Quadrilaterals
  • 13. Polygons
  • 14. Circles
  • 15. Coordinate Geometry
  • Mensuration
  • 16. 2D Mensuration
  • 17. 3D Mensuration
  • Trigonometry
  • 18. Introduction to Trigonometry
  • 19. Trigonometric Identities
  • 20. Heights and Distances
  • 21. Trigonometric Functions
  • 22. Inverse Trigonometric Functions
  • Advanced Algebra
  • 23. Sequences and Series
  • 24. Matrices
  • 25. Determinants
  • 26. Complex Numbers
  • 27. Permutations and Combinations
  • 28. Binomial Theorem
  • 29. Sets
  • 30. Relations
  • 31. Functions
  • Calculus
  • 32. Limits
  • 33. Continuity
  • 34. Differentiation
  • 35. Applications of Derivatives
  • 36. Integration
  • 37. Applications of Integrals
  • 38. Differential Equations
  • Vectors and 3D Geometry
  • 39. Vectors
  • Statistics and Probability
  • 40. Data Handling
    • 40.1. Introduction to Data
    • 40.2. Primary and Secondary Data
    • 40.3. Tabular Presentation of Data
    • 40.4. Graphical Representation (Bar Graphs, Histograms, Pie Charts)
    • 40.5. Frequency Distribution Tables
    • 40.6. Grouped and Ungrouped Data
  • 41. Measures of Central Tendency
  • 42. Measures of Dispersion
  • 43. Correlation
  • 44. Probability
  • 45. Random Variables
  • 46. Probability Distributions
  • Linear Programming
  • 47. Formulation of Linear Programming Problems
  • 48. Graphical Method
  • 49. Linear Programming - Constraints and Feasible Region
  • 50. Optimization Problems
  • Mathematical Reasoning
  • 51. Statements
  • 52. Logical Connectives
  • 53. Implications
  • 54. Validity of Statements and Arguments
Section Formula (Vector Form)Introduction to Data

Data Handling

Data handling explained with collection methods, organization, tables, charts, and simple examples for understanding statistical information.

1.Introduction to Data
Learn what data means, why it is collected, and how it helps in understanding information through simple, real-life examples.
2.Primary and Secondary Data
Understand primary and secondary data with simple notes-style explanations, clear definitions, and real-life examples.
3.Tabular Presentation of Data
Learn how to present data in tables with clear headings, rows, columns, and simple examples that make information easy to read and compare.
4.Graphical Representation (Bar Graphs, Histograms, Pie Charts)
Understand bar graphs, histograms, and pie charts with simple explanations, visuals in words, and clear examples to interpret data easily.
5.Frequency Distribution Tables
Learn what frequency means, how to create frequency tables for grouped and ungrouped data, and understand data distribution with simple examples.
6.Grouped and Ungrouped Data
Understand the difference between grouped and ungrouped data with clear explanations, simple examples, and easy-to-read notes.
Section Formula (Vector Form)Introduction to Data
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