Cambridge Mathematics IGCSE (US) Additional - Probability and Statistics
Course

Cambridge Mathematics IGCSE (US) Additional – Probability and Statistics

4.1 Probability
4.2 Discrete Random Variables
4.3 Descriptive Statistics
4.4 Exploring Data
4.5 Normal Distribution
4.6 Representing Data
4.7 Linear Modelling

38 Lessons
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Course Materials

PROBABILITY

Conditional Probability

Probabilities using Combinations

Binomial Probabilities

Expectation Theory

Expected Value

Fair Games and Expectation

Tables of Outcomes or Two-Way Tables

DISCRETE RANDOM VARIABLES

Discrete Random Variables

Dependent and Independent Variables

Discrete Probability Distributions

Expectation

DESCRIPTIVE STATISTICS

Populations and Samples

Samples and Sampling

Bias

EXPLORING DATA

Sample Standard Deviation

Outliers, Shapes and Skewness

Comparing Spread using Standard Deviation

Variance and Standard Deviation

NORMAL DISTRIBUTION

Normal Distribution

Probabilities using a calculator

Standard Normal Distribution

z-Scores

Using z-Scores to Compare Data

Applications of Normal Distribution

Properties of Normal Distribution

Inverse Cumulative Normal Distribution Quantiles

REPRESENTING DATA

Scatter Plots

LINEAR MODELLING

Linear Models

Correlation

Correlation Coefficient

Line of Best Fit