An XYZ business can currently produce 251 per hour of 5 amp fuses. The supplier claims that a new machine has been purchased and installed that will boost the manufacturing rate. The mean hourly production on the new machine was 259, with a sample standard deviation of 6 per hour, according to a sample of ten hours randomly selected from last month.
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\leq251"
"H_1:\\mu>251"
This corresponds to a right-tailed test, for which a t-test for one mean, with unknown population standard deviation, using the sample standard deviation, will be used.
Based on the information provided, the significance level is "\\alpha = 0.05,"
"df=n-1=10-1=9" degrees of freedom, and the critical value for a right-tailed test is "t_c =1.833113."
The rejection region for this right-tailed test is"R = \\{t: t > 1.833113\\}."
The t-statistic is computed as follows:
Since it is observed that "t = 4.21637 > 1.833113=t_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach: The p-value for right-tailed, "\\alpha=0.05, df=9, t=4.21637" is "p =0.001126," and since "p=0.001126<0.05=\\alpha," it is concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population mean "\\mu" is greater than 251, at the "\\alpha = 0.05" significance level.
Therefore, there is enough evidence to claim that the new machine is faster, at the "\\alpha = 0.05" significance level.
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