Answer:
The answer is 7,200...........
Answer:
The claim that the current work teams can build room additions quicker than the time allotted for by the contract has strong statistical evidence.
Step-by-step explanation:
We have to test the hypothesis to prove the claim that the work team can build room additions quicker than the time allotted for by the contract.
The null hypothesis is that the real time used is equal to the contract time. The alternative hypothesis is that the real time is less thant the allotted for by the contract.

The significance level, as a storng evidence is needed, is α=0.01.
The estimated standard deviation is:

As the standard deviation is estimated, we use the t-statistic with (n-1)=15 degrees of freedom.
For a significance level of 0.01, right-tailed test, the critical value of t is t=2.603.
Then, we calculate the t-value for this sample:

As the t-statistic lies in the rejection region, the null hypothesis is rejected. The claim that the current work teams can build room additions quicker than the time allotted for by the contract has strong statistical evidence.
Answer:
The lower confidence limit of 99% confidence interval for the mean breaking strength of the briefcases produced today would be equal to 331.09 pounds.
Step-by-step explanation:
Lower limit of confidence interval = mean - Error margin (E)
mean = 341.0 pounds
sd = 21.5 pounds
n = 35
degree of freedom = n - 1 = 35 - 1 = 34
confidence level = 99%
t-value corresponding to 34 degrees of freedom and 99% confidence level is 2.728
E = t × sd/√n = 2.728 × 21.5/√35 = 9.91 pounds
Lower limit = 341.0 - 9.91 = 331.09 pounds
<h3>Answer:</h3>
A
Step-by-step explanation:
{-32, 9, 11, 12}
first, find the mean (Find the sum of the data values, and divide the sum by the number of data values )
(-32) + 9 + 11 + 12 = 0
0/0 = 0
then, find the absolute value of the difference between each data value and the mean: |data value – mean|.
-32 - 0= -32
9 -0 = 9
11 -0 = 11
12 -0 = 0
finally, find the sum of the absolute values of the differences. Divide the sum of the absolute values of the differences by the number of data values.
0 - 0 / 4 = 0
answer is 0 (A)