• IB
  • IB Docs (2) Team
    Logout
  • Maths
  • Biology
  • Chemistry
  • Physics
  • Combined Science
  • English Language
  • Geography
  • Other Subjects
GCSE Maths
Edexcel Topic QuestionsRevision NotesPast PapersPast Papers Questions
AQA Topic QuestionsRevision NotesPast Papers
OCR Topic QuestionsRevision NotesPast Papers
GCSE Biology
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsRevision NotesPast Papers
OCR Gateway Topic QuestionsRevision NotesPast Papers
GCSE Chemistry
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsRevision NotesPast Papers
OCR Gateway Topic QuestionsRevision NotesPast Papers
GCSE Physics
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsRevision NotesPast Papers
OCR Gateway Topic QuestionsRevision NotesPast Papers
GCSE Combined Science
Edexcel Combined: Biology Topic QuestionsRevision NotesPast Papers
Edexcel Combined: Chemistry Topic QuestionsRevision NotesPast Papers
Edexcel Combined: Physics Revision NotesPast Papers
AQA Combined: Biology Topic QuestionsRevision NotesPast Papers
AQA Combined: Chemistry Topic QuestionsRevision NotesPast Papers
AQA Combined: Physics Topic QuestionsRevision NotesPast Papers
OCR Gateway Combined: Biology Topic QuestionsRevision Notes
OCR Gateway Combined: Chemistry Revision Notes
OCR Gateway Combined: Physics Revision Notes
GCSE English Language
AQA Revision NotesPractice PapersPast Papers
Edexcel Past Papers
OCR Past Papers
GCSE Geography
AQA Topic QuestionsRevision Notes
Edexcel Topic Questions
GCSE Other Subjects
AQA English LiteratureBusinessComputer ScienceEconomicsFurther MathsGeographyHistoryPsychologySociologyStatistics
Edexcel English LiteratureBusinessComputer ScienceGeographyHistoryPsychologyStatistics
OCR English LiteratureBusinessComputer ScienceEconomicsPsychology
OCR Gateway GeographyHistory
  • Maths
  • Biology
  • Chemistry
  • Physics
  • Double Science
  • Economics
  • English Language
  • Geography
  • Other Subjects
IGCSE Maths
Edexcel Topic QuestionsRevision NotesPast PapersBronze-Silver-Gold Questions
CIE (Extended) Topic QuestionsRevision NotesPast Papers
CIE (Core) Topic QuestionsPast Papers
IGCSE Biology
Edexcel Topic QuestionsRevision NotesPast Papers
CIE 2020-2022 Topic QuestionsRevision NotesPast Papers
CIE 2023-2025 Topic QuestionsRevision NotesPast Papers
IGCSE Chemistry
Edexcel Topic QuestionsRevision NotesPast Papers
CIE 2020-2022 Topic QuestionsRevision NotesPast Papers
CIE 2023-2025 Topic QuestionsRevision NotesPast Papers
IGCSE Physics
Edexcel Topic QuestionsRevision NotesPast Papers
CIE 2020-2022 Topic QuestionsRevision NotesPast Papers
CIE 2023-2025 Topic QuestionsRevision NotesPast Papers
IGCSE Double Science
Edexcel Double: Biology Topic QuestionsRevision NotesPast Papers
Edexcel Double: Chemistry Topic QuestionsRevision NotesPast Papers
Edexcel Double: Physics Topic QuestionsRevision NotesPast Papers
IGCSE Economics
CIE Topic QuestionsRevision NotesPast Papers
IGCSE English Language
CIE Revision NotesPractice PapersPast Papers
Edexcel Past Papers
IGCSE Geography
CIE Revision NotesTopic QuestionsPast Papers
Edexcel Topic QuestionsRevision NotesPast Papers
IGCSE Other Subjects
CIE Additional MathsEnglish LiteratureBusinessComputer ScienceHistorySociology
Edexcel English LiteratureBusinessComputer ScienceHistoryFurther Maths
  • Maths
  • Biology
  • Chemistry
  • Physics
  • English Language
  • Other Subjects
AS Maths
Edexcel Pure MathsMechanicsStatistics
AQA Pure MathsMechanicsStatistics
OCR Pure MathsMechanicsStatistics
CIE Pure 1Pure 2MechanicsProbability & Statistics 1
Edexcel IAS Pure 1Pure 2MechanicsStatistics
AS Biology
AQA Topic QuestionsRevision NotesPast Papers
OCR Topic QuestionsRevision NotesPast Papers
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Revision Notes
AS Chemistry
Edexcel Revision Notes
AQA Topic QuestionsRevision NotesPast Papers
OCR Revision Notes
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Revision Notes
AS Physics
Edexcel Revision Notes
AQA Topic QuestionsRevision NotesPast Papers
OCR Revision NotesPast Papers
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Revision Notes
AS English Language
AQA Past Papers
Edexcel Past Papers
OCR Past Papers
AS Other Subjects
AQA BusinessComputer ScienceEconomicsEnglish LiteratureFurther MathsGeographyHistoryPsychologySociology
Edexcel BusinessEconomicsEnglish LiteratureFurther MathsGeographyHistoryPsychology
OCR BusinessComputer ScienceEconomicsEnglish LiteratureFurther Maths AGeographyHistoryPsychologySociology
CIE Further Maths
  • Maths
  • Biology
  • Chemistry
  • Physics
  • English Language
  • Economics
  • Further Maths
  • Psychology
  • Other Subjects
A Level Maths
Edexcel Pure MathsMechanicsStatistics
AQA Pure MathsMechanicsStatistics
OCR Pure MathsMechanicsStatistics
CIE Pure 1Pure 3MechanicsProbability & Statistics 1Probability & Statistics 2
Edexcel IAL Pure 1Pure 2Pure 3Pure 4Mechanics 1Mechanics 2Statistics 1Statistics 2Decision 1
A Level Biology
Edexcel Topic QuestionsPast Papers
Edexcel A (SNAB) Revision Notes
AQA Topic QuestionsRevision NotesPast Papers
OCR Topic QuestionsRevision NotesPast PapersGold Questions
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Topic QuestionsRevision NotesPast Papers
A Level Chemistry
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsRevision NotesPast Papers
OCR Topic QuestionsRevision NotesPast PapersGold Questions
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Topic QuestionsRevision NotesPast Papers
A Level Physics
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsRevision NotesPast Papers
OCR Topic QuestionsRevision NotesPast Papers
CIE 2019-2021 Topic QuestionsRevision NotesPast Papers
CIE 2022-2024 Topic QuestionsRevision NotesPast Papers
Edexcel IAL Topic QuestionsRevision NotesPast Papers
A Level English Language
AQA Past Papers
CIE Past Papers
Edexcel Past Papers
OCR Past Papers
Edexcel IAL Past Papers
A Level Economics
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Topic QuestionsPast Papers
OCR Past Papers
CIE Past Papers
A Level Further Maths
Edexcel Topic QuestionsRevision NotesPast Papers
AQA Past Papers
OCR Past Papers
CIE Past Papers
Edexcel IAL Past Papers
A Level Psychology
AQA Topic QuestionsRevision NotesPast Papers
CIE Past Papers
Edexcel Past Papers
OCR Past Papers
Edexcel IAL Past Papers
A Level Other Subjects
AQA BusinessComputer ScienceEconomicsEnglish LiteratureGeographyHistorySociology
CIE BusinessComputer ScienceEconomicsEnglish LiteratureGeographySociology
Edexcel BusinessEconomics AEnglish LiteratureGeographyHistory
OCR BusinessComputer ScienceEconomicsEnglish LiteratureGeographyHistorySociology
Edexcel IAL English LiteratureGeography
CIE IAL History
  • Biology
  • Chemistry
  • Physics
  • Other Subjects
O Level Biology
CIE Topic QuestionsPast Papers
O Level Chemistry
CIE Topic QuestionsPast Papers
O Level Physics
CIE Topic QuestionsPast Papers
O Level Other Subjects
CIE Additional MathsMaths D
  • Maths
  • Biology
  • Chemistry
  • Physics
Pre U Maths
CIE Topic QuestionsPast Papers
Pre U Biology
CIE Topic QuestionsPast Papers
Pre U Chemistry
CIE Topic QuestionsPast Papers
Pre U Physics
CIE Topic QuestionsPast Papers
  • Maths
  • Biology
  • Chemistry
  • Physics
  • Economics
IB Maths
Maths: AA HL Topic QuestionsRevision NotesPractice Papers
Maths: AI HL Topic QuestionsRevision NotesPractice Papers
Maths: AA SL Topic QuestionsRevision NotesPractice Papers
Maths: AI SL Topic QuestionsRevision NotesPractice Papers
IB Biology
Biology: SL Topic QuestionsRevision NotesPractice Papers
Biology: HL Topic QuestionsRevision NotesPractice Papers
IB Chemistry
Chemistry: SL Topic QuestionsRevision NotesPractice Papers
Chemistry: HL Topic QuestionsRevision NotesPractice Papers
IB Physics
Physics: SL Topic QuestionsRevision NotesPractice Papers
Physics: HL Topic QuestionsRevision NotesPractice Papers
IB Economics
Economics: SL Revision Notes

DP IB Maths: AI HL

Revision Notes

Home / IB / Maths: AI HL / DP / Revision Notes / 4. Statistics & Probability / 4.9 Further Normal Distribution (inc Central Limit Theorem) / 4.9.1 Sample Mean Distribution


4.9.1 Sample Mean Distribution


Combinations of Normal Variables

What is a linear combination of normal random variables?

  • Suppose you have n independent normal random variables X subscript i tilde straight N invisible function application open parentheses mu subscript i comma blank sigma subscript i superscript 2 close parentheses for i = 1,2,3, ..., n
  • A linear combination is of the form X equals a subscript 1 X subscript 1 plus a subscript 2 X subscript 2 plus blank horizontal ellipsis plus a subscript n X subscript n plus b where ai and b are constants
  • The mean and variance can be calculated using results from random variables
    • straight E invisible function application open parentheses X close parentheses equals a subscript 1 mu subscript 1 plus a subscript 2 mu subscript 2 plus blank horizontal ellipsis plus a subscript n mu subscript n plus b
    • Var invisible function application open parentheses X close parentheses equals a subscript 1 superscript 2 sigma subscript 1 superscript 2 plus a subscript 2 superscript 2 sigma subscript 2 superscript 2 plus blank horizontal ellipsis plus a subscript n superscript 2 sigma subscript n superscript 2
      • The variables need to be independent for this result to be true
  • A linear combination of n independent normal random variables is also a normal random variable itself
    •  X tilde straight N invisible function application open parentheses a subscript 1 mu subscript 1 plus a subscript 2 mu subscript 2 plus blank horizontal ellipsis plus a subscript n mu subscript n plus b comma space a subscript 1 superscript 2 sigma subscript 1 superscript 2 plus a subscript 2 superscript 2 sigma subscript 2 superscript 2 plus blank horizontal ellipsis plus a subscript n superscript 2 sigma subscript n superscript 2 close parentheses
    • This can be used to find probabilities when combining normal random variables

What is meant by the sample mean distribution?

  • Suppose you have a population with distribution X and you take a random sample with n observations X1, X2, ..., Xn
  • The sample mean distribution is the distribution of the values of the sample mean
    • top enclose X equals fraction numerator X subscript 1 plus X subscript 2 plus blank horizontal ellipsis plus X subscript n over denominator n end fraction
  • For an individual sample the sample mean x with bar on top can be calculated
    • This is also called a point estimate
    • top enclose X is the distribution of the point estimates

What does the sample mean distribution look like when X is normally distributed?

  • If the population is normally distributed then the sample mean distribution is also normally distributed
  • straight E invisible function application open parentheses X with bar on top close parentheses equals straight E invisible function application open parentheses fraction numerator X subscript 1 plus X subscript 2 plus blank horizontal ellipsis plus X subscript n over denominator n end fraction close parentheses equals fraction numerator straight E invisible function application open parentheses X subscript 1 close parentheses plus straight E invisible function application open parentheses X subscript 2 close parentheses plus blank horizontal ellipsis plus straight E left parenthesis X subscript n right parenthesis over denominator n end fraction equals fraction numerator mu plus mu plus blank horizontal ellipsis plus mu over denominator n end fraction equals fraction numerator n mu over denominator n end fraction equals mu
  • Var invisible function application open parentheses X with bar on top close parentheses equals Var invisible function application open parentheses fraction numerator X subscript 1 plus X subscript 2 plus blank horizontal ellipsis plus X subscript n over denominator n end fraction close parentheses equals fraction numerator Var invisible function application open parentheses X subscript 1 close parentheses plus Var invisible function application open parentheses X subscript 2 close parentheses plus blank horizontal ellipsis plus Var left parenthesis X subscript n right parenthesis over denominator n ² end fraction equals fraction numerator sigma ² plus sigma ² plus blank horizontal ellipsis plus sigma ² over denominator n ² end fraction equals fraction numerator n sigma ² over denominator n ² end fraction equals sigma squared over n
  • Therefore you divide the variance of the population by the size of the sample to get the variance of the sample mean distribution
    • X tilde straight N invisible function application open parentheses mu comma sigma squared close parentheses rightwards double arrow X with bar on top tilde straight N invisible function application open parentheses mu comma sigma squared over n close parentheses

Worked Example

Amber makes a cup of tea using a hot drink vending machine. When the hot water button is pressed the machine dispenses  Wml of hot water and when the milk button is pressed the machine dispenses M ml of milk. It is known that W blank tilde straight N invisible function application open parentheses 100 comma blank 15 squared close parentheses and M blank tilde straight N invisible function application open parentheses 10 comma blank 2 squared close parentheses. 

To make a cup of tea Amber presses the hot water button three times and the milk button twice. The total amount of liquid in Amber’s cup is modelled by C ml.

a)
Write down the distribution of C.

4-9-1-ib-ai-hl-linear-normal-comb-a-we-solution

b)
Find the probability that the total amount of liquid in Amber's cup exceeds 360 ml.

4-9-1-ib-ai-hl-linear-normal-comb-b-we-solution

c)
Amber makes 15 cups of tea and calculates the mean C with bar on top. Write down the distribution of C with bar on top.

4-9-1-ib-ai-hl-linear-normal-comb-c-we-solution

Central Limit Theorem

What is the Central Limit Theorem?

  • The Central Limit Theorem says that if a sufficiently large random sample is taken from any distribution X then the sample mean distribution X with bar on top can be approximated by a normal distribution
    • In your exam n > 30 will be considered sufficiently large for the sample size
  • Therefore X with bar on top can be modelled by straight N invisible function application open parentheses mu comma sigma squared over n close parentheses
    • μ is the mean of X
    • σ² is the variance of X
    • n is the size of the sample

Do I always need to use the Central Limit Theorem when working with the sample mean distribution?

  • No – the Central Limit Theorem is not needed when the population is normally distributed
  • If X is normally distributed then X with bar on top is normally distributed
    • This is true regardless of the size of the sample
    • The Central Limit Theorem is not needed
  • If X is not normally distributed then X with bar on top is approximately normally distributed
    • Provided the sample size is large enough
    • The Central Limit Theorem is needed

Worked Example

The integers 1 to 29 are written on counters and placed in a bag. The expected value when one is picked at random is 15 and the variance is 70. Susie randomly picks 40 integers, returning the counter after each selection.

a)
Find the probability that the mean of Susie's 40 numbers is less than 13.

4-9-1-ib-ai-hl-central-limit-theorem-a-we-solution

b)
Explain whether it was necessary to use the Central Limit Theorem in your calculation.

4-9-1-ib-ai-hl-central-limit-theorem-b-we-solution



  • 1. Number & Algebra
    • 1.1 Number Toolkit
      • 1.1.1 Standard Form
        • 1.1.2 Approximation & Estimation
          • 1.1.3 GDC: Solving Equations
          • 1.2 Exponentials & Logs
            • 1.2.1 Exponents
              • 1.2.2 Logarithms
              • 1.3 Sequences & Series
                • 1.3.1 Language of Sequences & Series
                  • 1.3.2 Arithmetic Sequences & Series
                    • 1.3.3 Geometric Sequences & Series
                      • 1.3.4 Applications of Sequences & Series
                      • 1.4 Financial Applications
                        • 1.4.1 Compound Interest & Depreciation
                          • 1.4.2 Amortisation & Annuities
                          • 1.5 Complex Numbers
                            • 1.5.1 Intro to Complex Numbers
                              • 1.5.2 Modulus & Argument
                                • 1.5.3 Introduction to Argand Diagrams
                                • 1.6 Further Complex Numbers
                                  • 1.6.1 Geometry of Complex Numbers
                                    • 1.6.2 Forms of Complex Numbers
                                      • 1.6.3 Applications of Complex Numbers
                                      • 1.7 Matrices
                                        • 1.7.1 Introduction to Matrices
                                          • 1.7.2 Operations with Matrices
                                            • 1.7.3 Determinants & Inverses
                                              • 1.7.4 Solving Systems of Linear Equations with Matrices
                                              • 1.8 Eigenvalues & Eigenvectors
                                                • 1.8.1 Eigenvalues & Eigenvectors
                                                  • 1.8.2 Applications of Matrices
                                                • 2. Functions
                                                  • 2.1 Linear Functions & Graphs
                                                    • 2.1.1 Equations of a Straight Line
                                                    • 2.2 Further Functions & Graphs
                                                      • 2.2.1 Functions
                                                        • 2.2.2 Graphing Functions
                                                          • 2.2.3 Properties of Graphs
                                                          • 2.3 Modelling with Functions
                                                            • 2.3.1 Linear Models
                                                              • 2.3.2 Quadratic & Cubic Models
                                                                • 2.3.3 Exponential Models
                                                                  • 2.3.4 Direct & Inverse Variation
                                                                    • 2.3.5 Sinusoidal Models
                                                                      • 2.3.6 Strategy for Modelling Functions
                                                                      • 2.4 Functions Toolkit
                                                                        • 2.4.1 Composite & Inverse Functions
                                                                        • 2.5 Transformations of Graphs
                                                                          • 2.5.1 Translations of Graphs
                                                                            • 2.5.2 Reflections of Graphs
                                                                              • 2.5.3 Stretches of Graphs
                                                                                • 2.5.4 Composite Transformations of Graphs
                                                                                • 2.6 Further Modelling with Functions
                                                                                  • 2.6.1 Properties of Further Graphs
                                                                                    • 2.6.2 Natural Logarithmic Models
                                                                                      • 2.6.3 Logistic Models
                                                                                        • 2.6.4 Piecewise Models
                                                                                      • 3. Geometry & Trigonometry
                                                                                        • 3.1 Geometry Toolkit
                                                                                          • 3.1.1 Coordinate Geometry
                                                                                            • 3.1.2 Radian Measure
                                                                                              • 3.1.3 Arcs & Sectors
                                                                                              • 3.2 Geometry of 3D Shapes
                                                                                                • 3.2.1 3D Coordinate Geometry
                                                                                                  • 3.2.2 Volume & Surface Area
                                                                                                  • 3.3 Trigonometry
                                                                                                    • 3.3.1 Pythagoras & Right-Angled Triganometry
                                                                                                      • 3.3.2 Non Right-Angled Trigonometry
                                                                                                        • 3.3.3 Applications of Trigonometry & Pythagoras
                                                                                                        • 3.4 Further Trigonometry
                                                                                                          • 3.4.1 The Unit Circle
                                                                                                            • 3.4.2 Simple Identities
                                                                                                              • 3.4.3 Solving Trigonometric Equations
                                                                                                              • 3.5 Voronoi Diagrams
                                                                                                                • 3.5.1 Voronoi Diagrams
                                                                                                                  • 3.5.2 Toxic Waste Dump Problem
                                                                                                                  • 3.6 Matrix Transformations
                                                                                                                    • 3.6.1 Matrix Transformations
                                                                                                                      • 3.6.2 Determinant of a Transformation Matrix
                                                                                                                      • 3.7 Vector Properties
                                                                                                                        • 3.7.1 Introduction to Vectors
                                                                                                                          • 3.7.2 Position & Displacement Vectors
                                                                                                                            • 3.7.3 Magnitude of a Vector
                                                                                                                              • 3.7.4 The Scalar Product
                                                                                                                                • 3.7.5 The Vector Product
                                                                                                                                  • 3.7.6 Components of Vectors
                                                                                                                                    • 3.7.7 Geometric Proof with Vectors
                                                                                                                                    • 3.8 Vector Equations of Lines
                                                                                                                                      • 3.8.1 Vector Equations of Lines
                                                                                                                                        • 3.8.2 Shortest Distances with Lines
                                                                                                                                        • 3.9 Modelling with Vectors
                                                                                                                                          • 3.9.1 Kinematics with Vectors
                                                                                                                                            • 3.9.2 Constant & Variable Velocity
                                                                                                                                            • 3.10 Graph Theory
                                                                                                                                              • 3.10.1 Introduction to Graph Theory
                                                                                                                                                • 3.10.2 Walks & Adjacency Matrices
                                                                                                                                                  • 3.10.3 Minimum Spanning Trees
                                                                                                                                                    • 3.10.4 Chinese Postman Problem
                                                                                                                                                      • 3.10.5 Travelling Salesman Problem
                                                                                                                                                        • 3.10.6 Bounds for Travelling Salesman Problem
                                                                                                                                                      • 4. Statistics & Probability
                                                                                                                                                        • 4.1 Statistics Toolkit
                                                                                                                                                          • 4.1.1 Sampling
                                                                                                                                                            • 4.1.2 Data Collection
                                                                                                                                                              • 4.1.3 Statistical Measures
                                                                                                                                                                • 4.1.4 Frequency Tables
                                                                                                                                                                  • 4.1.5 Linear Transformations of Data
                                                                                                                                                                    • 4.1.6 Outliers
                                                                                                                                                                      • 4.1.7 Univariate Data
                                                                                                                                                                        • 4.1.8 Interpreting Data
                                                                                                                                                                        • 4.2 Correlation & Regression
                                                                                                                                                                          • 4.2.1 Bivariate Data
                                                                                                                                                                            • 4.2.2 Correlation Coefficients
                                                                                                                                                                              • 4.2.3 Linear Regression
                                                                                                                                                                              • 4.3 Further Correlation & Regression
                                                                                                                                                                                • 4.3.1 Non-linear Regression
                                                                                                                                                                                  • 4.3.2 Logarithmic Scales
                                                                                                                                                                                    • 4.3.3 Linearising using Logarithms
                                                                                                                                                                                    • 4.4 Probability
                                                                                                                                                                                      • 4.4.1 Probability & Types of Events
                                                                                                                                                                                        • 4.4.2 Conditional Probability
                                                                                                                                                                                          • 4.4.3 Sample Space Diagrams
                                                                                                                                                                                          • 4.5 Probability Distributions
                                                                                                                                                                                            • 4.5.1 Discrete Probability Distributions
                                                                                                                                                                                              • 4.5.2 Expected Values
                                                                                                                                                                                              • 4.6 Random Variables
                                                                                                                                                                                                • 4.6.1 Linear Combinations of Random Variables
                                                                                                                                                                                                  • 4.6.2 Unbiased Estimates
                                                                                                                                                                                                  • 4.7 Binomial Distribution
                                                                                                                                                                                                    • 4.7.1 The Binomial Distribution
                                                                                                                                                                                                      • 4.7.2 Calculating Binomial Probabilities
                                                                                                                                                                                                      • 4.8 Normal Distribution
                                                                                                                                                                                                        • 4.8.1 The Normal Distribution
                                                                                                                                                                                                          • 4.8.2 Calculations with Normal Distribution
                                                                                                                                                                                                          • 4.9 Further Normal Distribution (inc Central Limit Theorem)
                                                                                                                                                                                                            • 4.9.1 Sample Mean Distribution
                                                                                                                                                                                                              • 4.9.2 Confidence Interval for the Mean
                                                                                                                                                                                                              • 4.10 Poisson Distribution
                                                                                                                                                                                                                • 4.10.1 Poisson Distribution
                                                                                                                                                                                                                  • 4.10.2 Calculating Poisson Probabilities
                                                                                                                                                                                                                  • 4.11 Hypothesis Testing
                                                                                                                                                                                                                    • 4.11.1 Hypothesis Testing
                                                                                                                                                                                                                      • 4.11.2 Chi-squared Test for Independence
                                                                                                                                                                                                                        • 4.11.3 Goodness of Fit Test
                                                                                                                                                                                                                        • 4.12 Further Hypothesis Testing
                                                                                                                                                                                                                          • 4.12.1 Hypothesis Testing for Mean (One Sample)
                                                                                                                                                                                                                            • 4.12.2 Hypothesis Testing for Mean (Two Sample)
                                                                                                                                                                                                                              • 4.12.3 Binomial Hypothesis Testing
                                                                                                                                                                                                                                • 4.12.4 Poisson Hypothesis Testing
                                                                                                                                                                                                                                  • 4.12.5 Hypothesis Testing for Correlation
                                                                                                                                                                                                                                    • 4.12.6 Type I & Type II Errors
                                                                                                                                                                                                                                    • 4.13 Transition Matrices & Markov Chains
                                                                                                                                                                                                                                      • 4.13.1 Markov Chains
                                                                                                                                                                                                                                        • 4.13.2 Transition Matrices
                                                                                                                                                                                                                                      • 5. Calculus
                                                                                                                                                                                                                                        • 5.1 Differentiation
                                                                                                                                                                                                                                          • 5.1.1 Introduction to Differentiation
                                                                                                                                                                                                                                            • 5.1.2 Applications of Differentiation
                                                                                                                                                                                                                                              • 5.1.3 Modelling with Differentiation
                                                                                                                                                                                                                                              • 5.2 Further Differentiation
                                                                                                                                                                                                                                                • 5.2.1 Differentiating Special Functions
                                                                                                                                                                                                                                                  • 5.2.2 Techniques of Differentiation
                                                                                                                                                                                                                                                    • 5.2.3 Related Rates of Change
                                                                                                                                                                                                                                                      • 5.2.4 Second Order Derivatives
                                                                                                                                                                                                                                                        • 5.2.5 Further Applications of Differentiation
                                                                                                                                                                                                                                                          • 5.2.6 Concavity & Points of Inflection
                                                                                                                                                                                                                                                          • 5.3 Integration
                                                                                                                                                                                                                                                            • 5.3.1 Trapezoid Rule: Numerical Integration
                                                                                                                                                                                                                                                              • 5.3.2 Introduction to Integration
                                                                                                                                                                                                                                                                • 5.3.3 Applications of Integration
                                                                                                                                                                                                                                                                • 5.4 Further Integration
                                                                                                                                                                                                                                                                  • 5.4.1 Integrating Special Functions
                                                                                                                                                                                                                                                                    • 5.4.2 Techniques of Integration
                                                                                                                                                                                                                                                                      • 5.4.3 Further Applications of Integration
                                                                                                                                                                                                                                                                        • 5.4.4 Volumes of Revolution
                                                                                                                                                                                                                                                                        • 5.5 Kinematics
                                                                                                                                                                                                                                                                          • 5.5.1 Kinematics Toolkit
                                                                                                                                                                                                                                                                            • 5.5.2 Calculus for Kinematics
                                                                                                                                                                                                                                                                            • 5.6 Differential Equations
                                                                                                                                                                                                                                                                              • 5.6.1 Modelling with Differential Equations
                                                                                                                                                                                                                                                                                • 5.6.2 Separation of Variables
                                                                                                                                                                                                                                                                                  • 5.6.3 Slope Fields
                                                                                                                                                                                                                                                                                    • 5.6.4 Approximate Solutions to Differential Equations
                                                                                                                                                                                                                                                                                    • 5.7 Further Differential Equations
                                                                                                                                                                                                                                                                                      • 5.7.1 Coupled Differential Equations
                                                                                                                                                                                                                                                                                        • 5.7.2 Second Order Differential Equations
                                                                                                                                                                                                                                                                                      Daniel Finlay

                                                                                                                                                                                                                                                                                      Author: Daniel

                                                                                                                                                                                                                                                                                      Dan graduated from the University of Oxford with a First class degree in mathematics. As well as teaching maths for over 8 years, Dan has marked a range of exams for Edexcel, tutored students and taught A Level Accounting. Dan has a keen interest in statistics and probability and their real-life applications.


                                                                                                                                                                                                                                                                                      Save My Exams Logo
                                                                                                                                                                                                                                                                                      Resources
                                                                                                                                                                                                                                                                                      Home Join Support

                                                                                                                                                                                                                                                                                      Members
                                                                                                                                                                                                                                                                                      Members Home Account Logout

                                                                                                                                                                                                                                                                                      Company
                                                                                                                                                                                                                                                                                      About Us Contact Us Jobs Terms Privacy Facebook Twitter

                                                                                                                                                                                                                                                                                      Quick Links
                                                                                                                                                                                                                                                                                      GCSE Revision Notes IGCSE Revision Notes A Level Revision Notes Biology Chemistry Physics Maths 2022 Advance Information

                                                                                                                                                                                                                                                                                       
                                                                                                                                                                                                                                                                                      © IB Documents (2) Team & u/aimlesskr
                                                                                                                                                                                                                                                                                      IBO was not involved in the production of, and does not endorse, the resources created by Save My Exams.