Answer:
The 95% confidence interval estimate for the population mean force is (1691, 1755).
Explanation:
According to the Central Limit Theorem if we have an unknown population with mean μ and standard deviation σ and appropriately huge random samples (n > 30) are selected from the population with replacement, then the distribution of the sample mean will be approximately normally.
The sample selected here is n = 30.
Thus, the sampling distribution of the sample mean will be normal.
Compute the sample mean and standard deviation as follows:
![\bar x=(1)/(n)\sum x=(1)/(30)* 51702=1723.4\\\\s=\sqrt{(1)/(n-1)\sum (x-\bar x)^(2)}=\sqrt{(1)/(30-1)* 232561.2}=89.55](https://img.qammunity.org/2021/formulas/mathematics/college/j4wga2o2jypuh43pyvxly0jh1o17rs0afn.png)
Construct a 95% confidence interval estimate for the population mean force as follows:
![CI=\bar x\pm z_(\alpha /2)*(s)/(√(n))](https://img.qammunity.org/2021/formulas/mathematics/college/33t312b5iqxguo597j8ieao36fboixb7zc.png)
![=1723.4\pm 1.96*(89.55)/(√(30))\\\\=1723.4\pm 32.045\\\\=(1691.355, 1755.445)\\\\\approx (1691, 1755)](https://img.qammunity.org/2021/formulas/mathematics/college/ryp7zakij0xlghlmdt33ohgmfw2szewjx5.png)
Thus, the 95% confidence interval estimate for the population mean force is (1691, 1755).