MHB Statistical Significance: Manufacturer's Claim Rejected?

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The discussion centers on evaluating the statistical significance of a manufacturer's claim that only 1% of their laptops are defective, in light of a sample showing 3% defects. The evidence suggests that obtaining a sample defect rate of 3% would occur with less than a 0.1% probability if the true defect rate were indeed 1%. This low probability indicates that the observed defect rate is unlikely to be due to random chance. Therefore, there is statistically significant evidence against the manufacturer's claim of a 1% defect rate. The conclusion drawn is that the sample results provide strong grounds to question the accuracy of the manufacturer's assertion.
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form a conclusion about statistical significance. Do not make any formal calculations. Either use the results provided or make subjective judgments about the results.

a manufacturer of laptop computers claims that only 1% of their computers are defective. In a sample of 600 computers, it was found that 3% were defective. If the proportion of defectives were really only 1%, there would be less than 1 chance in 1000 of getting such a large proportion of defective laptops in the sample. Is there statistically significant evidence against the manufacturer's claim ? Why or why not?
 
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"If the proportion of defectives were really only 1%, there would be less than 1 chance in 1000 of getting such a large proportion of defective laptops in the sample. "

So what do you think? Is getting a result that is so unlikely to happen by chance "statistically significant"?
 

Thread 'Significant figures for inherently bound values'

I have been insisting to my statistics students that for probabilities, the rule is the number of significant figures is the number of digits past the leading zeros or leading nines. For example to give 4 significant figures for a probability: 0.000001234 and 0.99999991234 are the correct number of decimal places. That way the complementary probability can also be given to the same significant figures ( 0.999998766 and 0.00000008766 respectively). More generally if you have a value that...
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