A manufacturer claims that the average weight of a tin of baked beans in 440g and the standard deviation is known to be 20g. From a random sample of 100 cans you calculate the average weight to be 435g. At the 95% level of confidence, is there a change in the average weight of a can of baked beans?
"\\mu = 440 \\\\\n\n\\sigma = 20 \\\\\n\nn = 100 \\\\\n\n\\bar{x} = 435 \\\\\n\n\u03b1 = 0.05 \\\\\n\nH_0 : \\mu = 440 \\\\\n\nH_1 : \\mu \u2260 440"
Test concerning averages
"z = \\frac{\\bar{x}- \\mu}{\\sigma \/ \\sqrt{n}} \\\\\n\nz = \\frac{435-440}{20\/ \\sqrt{100}} = -2.5"
Critical value at 0.05 significance level with 99 d.f. z = ±1.96
Critical regions: Two-tailed test. Reject H0 if z ≤ -1.96 or z≥1.96
Conclusion: Since z = -2.5 is less than -1.96, reject the null hypothesis at the 95% level of confidence. There is a change in the average weight of a can of baked beans.
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