Skip to content

Course home

2.5 Statistical Hypothesis Testing

2.5 Statistical Hypothesis Testing

EasyMediumHard
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273
Question 219

A precision engineering firm manufactures silicon wafers. The existing process is specified to have a thickness with a variance of 6 μm26\ \mu m^26 μm2. An engineer suspects that the variance has recently increased due to machine wear.

Ten wafers are randomly selected and their thicknesses are measured, yielding the following results in micrometers:

254,248,251,247,252,250,246,253,255,244 254, 248, 251, 247, 252, 250, 246, 253, 255, 244 254,248,251,247,252,250,246,253,255,244
a.

Calculate the sample mean, xˉ\bar{x}xˉ, and the sample variance, s2s^2s2, for these measurements.

[3]
b.

Assume that the thicknesses follow a normal distribution.

Test the engineer's suspicion at the 5% significance level, using the hypotheses H0:σ2=6H_0: \sigma^2 = 6H0​:σ2=6 and H1:σ2>6H_1: \sigma^2 > 6H1​:σ2>6.

[4]
c.

A technician introduces a new calibration method which they believe reduces the variance. They provide a sample of 15 wafers where the calculated sample variance is s2=1.95s^2 = 1.95s2=1.95.

Use this value of s2s^2s2 to calculate a 90% confidence interval for the variance, σ2\sigma^2σ2, for wafers produced using the new calibration method.

[You may use P(χ142>6.571)=0.95P(\chi_{14}^2 > 6.571) = 0.95P(χ142​>6.571)=0.95 and P(χ142>23.685)=0.05P(\chi_{14}^2 > 23.685) = 0.05P(χ142​>23.685)=0.05]

[3]
d.

Given the original process variance of σ2=6\sigma^2 = 6σ2=6, evaluate the technician's claim regarding the new calibration method.

[2]
Markscheme

2.5 Statistical Hypothesis Testing Questions

  1. A Level
  2. /Maths
  3. /2.5 Statistical Hypothesis Testing

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.

Question bank