Unit 4
14 dot points, in syllabus order. Each dot point has a focused answer, with exam-style questions and worked answers where available.
How does the Fundamental Theorem of Calculus link differentiation and integration into inverse processes?
What controls the width of a confidence interval, and how large must a sample be to achieve a required precision?
What are the defining properties of the normal distribution and the empirical 68-95-99.7 rule?
How does the sample proportion behave across repeated random samples, and why is it approximately normal?
How does a probability density function describe a continuous random variable, and how do we find probabilities from it?
How do we use integration to recover velocity and displacement from acceleration, and find distance travelled?
How do we find the area enclosed between two curves, including where they cross?
How do we standardise a normal variable and calculate normal probabilities, including inverse problems?
How is the definite integral defined as a limit of sums, and why does it give signed area under a curve?
How do we recover the total change in a quantity from its rate of change?
How do we model continuous data using probability density functions and the normal distribution?
How do we use a sample proportion to estimate a population proportion with a confidence interval?
How do we reverse differentiation to find areas, total change and other quantities through integration?
What does it mean to reverse differentiation, and how do we find the family of antiderivatives of a function?
