Question

if the mean from test 1 is 0.1 less than the mean fromtest 2, it is important to detect this with probability at least0.90. was the use of eight alloys an adequate sample size?if not, how many alloys should have been used?

Answer 1

Calculating the appropriate sample size for detecting a difference in means with high probability involves a power analysis, which requires variables such as effect size, standard deviation, and confidence level.

Step-by-step explanation:

The question pertains to determining if an adequate sample size was used to detect a difference in means between two tests with a specified level of confidence. Determining the appropriate sample size depends on several factors, including the desired level of confidence, the acceptable margin of error, and the standard deviation of the population.

In statistical hypothesis testing, power analysis is often used to calculate the minimum sample size required to detect an effect of a given size with a certain degree of confidence.

To answer whether the use of eight alloys was an adequate sample size to detect a mean difference of 0.1 with at least 0.90 probability, we would conduct a power analysis. If the sample size is too small, the test may not have enough power to detect a difference.

A common approach would involve using software to simulate or calculate the necessary sample size based on input parameters such as effect size, standard deviation, and desired power level.If you have the necessary information, such as the standard deviation and effect size, you can use power analysis to determine the sample size required to achieve a desired level of power.