H1 Mathematics course check
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Learning goals
- Reason about sampling and sampling distributions
- Classify stationary points using justified derivative tests
- Apply the chain rule to composite functions
- Find antiderivatives within the permitted scope
- Calculate an event probability in a specified binomial model
- Calculate the expectation of a specified binomial count
- Calculate the variance of a specified binomial count
- Calculate a conditional probability in a specified binomial model
- Calculate a conditional probability in a specified normal model
- Calculate and interpret conditional probabilities
- Evaluate definite integrals
- Differentiate within the permitted function scope
- Calculate an estimated standard error from a specified independent sample
- Calculate event probabilities from an explicit sample space
- Calculate a linear combination's variance with justified dependence conditions
- Calculate a linear combination's expectation from specified moments
- Calculate original-input solution of a specified fitted calibration model from specified paired data
- Calculate complete ordered intercept and gradient from specified paired data
- Calculate product-moment correlation from specified paired data
- Calculate original-response model prediction from specified paired data
- Calculate signed residual on the fitted response scale from specified paired data
- Calculate sum of squared residuals on the fitted response scale from specified paired data
- Calculate a probability for a specified combination of normal variables
- Calculate an event probability in a specified normal model
- Recover a normal boundary from its specified tail probability
- Calculate a sample-mean probability under a specified exact or approximate normal model
- Find the complete tangent to a polynomial at a stated input
- Calculate all sample-mean critical boundaries for a planned known-variance normal test
- Calculate all standardised critical boundaries for a planned population-mean test
- Calculate a population-mean test p-value for a prespecified alternative
- Calculate a signed population-mean test statistic under a stipulated normal-test model
- Find complete exponential antiderivatives on the stated interval
- Differentiate exponential compositions on the stated input interval
- Differentiate logarithmic compositions on the stated input interval
- Find complete mixed antiderivatives on the stated interval
- Differentiate mixed function sums on the stated input interval
- Find complete power antiderivatives on the stated interval
- Differentiate power sums on the stated input interval
- Find complete logarithmic antiderivatives on the stated interval
- Find a complete second derivative on the stated input interval
- Calculate a sample mean's expectation from specified population moments
- Calculate a sample mean's variance from specified population moments
- Calculate a minimum sample size for specified normal-model precision
- Calculate a sample mean's standard error from specified population moments
- Find and classify every stationary point of a polynomial
- Formulate and interpret a justified hypothesis test
- Use counting principles, permutations and combinations
- Determine a population-mean test decision using the unrounded planned p-value and level
- Distinguish independence from mutual exclusivity
- Calculate a population-mean estimate from a specified independent sample
- Calculate an unbiased population-variance estimate from a specified independent sample
- Evaluate a polynomial definite integral with linked exact working
- Find the least trial count satisfying a binomial probability threshold
- Find the greatest polynomial value and every attaining input on a closed interval
- Find the least polynomial value and every attaining input on a closed interval
- Find and interpret a tangent to a curve
- Fit and interpret correlation and regression models
- Formulate, use and interpret a mathematical model
- Relate a definite integral to area under a curve
- Interpret a derivative as gradient or rate of change
- Use quadratic structure and discriminants to reason about roots
- Interpret a function as one output for each input
- Choose and use a binomial probability model
- Model and interpret exponential and logarithmic relationships
- Choose and use a normal probability model
- Recover the unique binomial parameters from exact moments
- Recover a normal mean from a probability and known variance
- Recover the unique normal mean and variance from two probabilities
- Recover a normal variance from a probability and known mean
- Interpret and draw graphs of functions
- Solve inequalities and represent their solution sets
- Model and solve an optimisation problem
- Solve quadratic equations by suitable methods
- Solve simultaneous equations by justified methods
- Use logarithm laws with domain conditions
- Represent random variables, expectations and variances
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GCE A-Level H1 Mathematics 2027
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H1 Mathematics 2024
Course check
Start here to see which parts you already know.
Time is up and your answers could not be submitted; check your connection and try again.
Paper instructions
This shows what to work on next and doesn’t count towards your course progress.
- Question count is checked before you start.
- Feedback appears after you finish and submit.
Your work
Without an account, unfinished answers stay in this tab. Signed in, they are saved on this device until the deadline shown when you start.
Getting your questions…
Recent attempts
History is stored only in this browser.
No completed attempts are saved yet.
Beyond the syllabus: optional enrichment that does not count towards your progress.