Unit 3 & 4
Mathematical Methods (Victoria)
Differentiation & Applications
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					  Derivatives of Exponential, Logarithmic and Trigonmetric functions
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					  Joining two functions so that their gradients match: Part 1 (Maths Methods PSMT IA1 prep)
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					  Joining two functions so that their gradients match: Part 2 (Maths Methods PSMT IA1 prep)
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					  The chain rule revisited
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					  The Product Rule Revisited
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					  The quotient rule
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					  Equations of tangents and normals revisited
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					  Average vs instantaneous rates of change
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					  Rates of change application
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					  Motion in a straight line An application of rates
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					  Motion in a straight line acceleration recap
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					  Finding Stationary points
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					  Nature of Stationary points
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					  Sketching the derivative function from a picture
Integration
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					  Intro to Integration and integrating polynomials
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					  Integration a little bit of theory
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					  Integration finding the c value
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					  Integration the reverse chain rule
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					  Integration resulting in a logarithm
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					  Integrals of exponentials
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					  Integration of trig functions
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					  Integration by recognition updated
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					  Applications of Integration in motion questions
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					  The definite integral
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					  The definite integral signed area
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					  Area between two curves
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					  The area under a derivative function
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					  Trapezoidal Rule Fully explained
Discrete Random Variables & their Distributions
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					  Discrete Random Variables
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					  Discrete Random Distributions Expected value
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					  Probability Distributions Discrete vs continuous random variables
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					  Discrete Probability distributions 2 Properties of discrete probability distributions
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					  Discrete probability distribution 3 Graphing the distribution
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					  Discrete probability distributions 4 Applications
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					  Discrete random distributions Expected value challenging but important
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					  Discrete Random Variables including conditional probability
The Binomial Distribution
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					  Bernoulli sequence
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					  Binomial distribution introduction
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					  Developing Binomial Distribution Intuition
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					  The binomial Probability Formula
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					  Binomial Probability Distribution formula Worked Example
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					  Binomial Probability formula at most and at least
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					  Binomial Distribution on the Casio FX CG50AU
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					  Binomial Probability Conditional Probability
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					  Binomial distribution expected value variance and standard deviation
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					  Construct a Binomial Distribution Graph
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					  Binomial Distribution finding a sample size
Continuous Random Variables & The Normal Distribution
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					  Estimating probability of a continuous random variable using data
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					  The probability Density Function
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					  Mathematical proof that you do not exist
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					  Calculating probability using a probability density function
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					  Proving a function is a probability density function
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					  unknowns in probability density functions
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					  Unbounded Probability density functions
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					  The mean of a continuous random variable
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					  Calculating percentiles from a probability density function
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					  Calculating variance and standard deviation of a continuous random variable
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					  The Cumulative Probability Distribution Function
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					  The normal distribution Introduction
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					  Determining normal probabilities on the casio fx cg50AU
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					  The Inverse Normal Distribution on the Casio FX CG50AU
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					  The inverse normal distribution on the TI Nspire
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					  A tricky normal distribution question
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					  Using z scores to standardise and compare values
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					  The Normal Approximation to the binomial distribution
Sampling & Estimation
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					  Why is sample proportion interesting and important
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					  Sampling from a small population
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					  Sampling from a large population
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					  Sample proportion mean and standard deviation
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					  Approximating the distribution of sample proportions using the normal distribution
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					  Confidence Intervals for Population proportion
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					  Finding a confidence interval on the Casio FXCG50 AU Calculator
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					  Determining required Sample size for a given Margin of error
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					  Binomial Approximation to the normal and sample proportion, one question two ways

 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													 
	
													