Answer:
Explanation:
From the given information:
Let assume:
population mean for catalyst 1
population mean for catalyst 2
Then:
Null hypothesis:
![\mu_1 \ge \mu_2](https://img.qammunity.org/2022/formulas/mathematics/college/oms8qvqq8b3jhxl7doqz6bj345rc9su3lq.png)
Alternative hypothesis:
![\mu_1 <\mu_2](https://img.qammunity.org/2022/formulas/mathematics/college/7l7p6hs8o9yzjdq3sghu52fv8qrxr9sbs4.png)
![\alpha= 0.01](https://img.qammunity.org/2022/formulas/mathematics/college/x8dy9r8u27am0csuoy23npqgiffuk9h1ep.png)
By using MINITAB software to compute the 2 sample t-test, we have:
Two-Sample T_Test and CI
Sample N Mean StDev SE Mean
1 12 94.00 3.00 0.87
2 15 90.00 2.00 0.52
Difference =
![\mu_1(1)-\mu_2(2)](https://img.qammunity.org/2022/formulas/mathematics/college/zcksorkcm6787igpoaj4iqel7vpjm06knb.png)
Estimate of difference: -6.00
99% upper bound for difference: -3.603
T-test of difference: 0 (vs <): T-value = -6.22
P.value = 0.000
DF = 25
Both use Pooled StDev = 2.4900
From above result
the test statistics = -6.00
p-value = 0.00
Decision Rule: To reject
![H_o\ \ if \ \ p \le \alpha](https://img.qammunity.org/2022/formulas/mathematics/college/uvxj7qw69loit0fawaky78v6emvf163w5f.png)
Conclusion: Provided that p-value is < ∝, we reject
. Hence, there is sufficient evidence to support the given claim.
b) From the MINITAB;
The 99% C.I on the difference in the mean yields that can be applied to test the claim in part (a) is:
![\mathbf{\mu_1 -\mu_2 \le -3.60}](https://img.qammunity.org/2022/formulas/mathematics/college/ezmow0hox0izvqkbkknffst591hx036ip2.png)