An industrial ceramicist measures the energy consumption, EEE kWh, required to maintain different operating temperatures, TTT ∘C^{\circ}\text{C}∘C, in a specialized kiln. Data from 6 test runs are recorded in the table below.
| Run | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| TTT | 200 | 250 | 300 | 350 | 400 | 450 |
| EEE | 45 | 58 | 68 | 82 | 95 | 102 |
Calculate the values of STTS_{TT}STT, SEES_{EE}SEE and STES_{TE}STE for these measurements.
Calculate the product moment correlation coefficient (PMCC) for these data.
Interpret your result from part (b) in the context of the kiln's operation.
On a suitable grid, draw a scatter diagram of energy consumption against operating temperature for these 6 runs.
Determine the equation of the regression line of EEE on TTT in the form E=a+bTE = a + bTE=a+bT.
Use your regression line to estimate the energy consumption for a run with an operating temperature of 320 ∘C^{\circ}\text{C}∘C.
355 exam-style questions on OCR (MEI) A Level Maths 2.5 Statistical Hypothesis Testing, covering 2.5.1 Process and language of hypothesis testing, 2.5.2 When to apply 1-tail and 2-tail tests, 2.5.3 Significance level and incorrect rejection, 2.5.4 Null and alternative hypotheses (binomial), 2.5.5 Conduct a binomial hypothesis test, 2.5.6 Critical and acceptance regions (binomial), 2.5.7 Distribution of the sample mean (A-level only), 2.5.8 Hypothesis test for a single mean (A-level only), 2.5.9 Critical and acceptance regions (mean) (A-level only), 2.5.10 Correlation as closeness to a straight line (A-level only), 2.5.11 Inference using a correlation coefficient (A-level only), and 2.5 Statistical Hypothesis Testing. Each one has a worked solution and a mark scheme showing where the marks go.