A manufacturer of sprinkler systems designed for fire protection claims that the average activating temperature is 135 to test this claim, you randomly selected a sample of 32 systems and find evidence to reject the manufacturer's be 135.7 with a standard deviation of 3.3 at a=0.10, do you have enough evidence to reject the manufacturer's claim?
Hypothesized Population Mean "\\mu=135"
Population Standard Deviation "\\sigma=3.3"
Sample Size "n=32"
Sample Mean "\\bar{x}=135.7"
Significance Level "\\alpha=0.10"
Null and Alternative Hypotheses
The following null and alternative hypotheses need to be tested:
"H_0: \\mu=135"
"H_1: \\mu\\not=135"
This corresponds to two-tailed test, for which a z-test for one mean, with known population standard deviation will be used.
Based on the information provided, the significance level is "\\alpha=0.10," and the critical value for two-tailed test is "z_c=1.6449."
The rejection region for this two-tailed test is "R=\\{z:|>1.6449\\}."
The "z" - statistic is computed as follows:
Since it is observed that "|z|=1.19994<1.6449=z_c," it is then concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu" is different than "135," at the "\\alpha=0.01" significance level.
Using the P-value approach: The p-value for two-tailed, the significance level "\\alpha=0.10, z=1.19994," is "p=2P(Z>1.19994)=0.230163," and since "p=0.230163>0.10=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu" is different than "135," at the "\\alpha=0.10" significance level.
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