I occasionally stop at gas stations that have "free air" and make sure the pressure in my tires is correct. My tires are supposed to have 35 pounds of pressure per square inch. When I connect the hose to my valve the device reads the pressure that is currently in the tire and adds air, if needed, to bring the tire to the pressure that I request. It is important that the pump gauge works properly and does not put in too much or too little air.

An inspector checks the air pump twice a year to make sure it is working properly. She connects the air pump to a device that is set to output 35 pounds of pressure and records what the pump gauge displays as the pressure. She repeats this process 10 times.

A graph of the data is roughly symmetric with no outliers. The 99% confidence interval for the true mean pressure detected is 33.5 to 34.8 pounds per square inch. He needs to determine if the pump needs to be repaired.

What conclusion would you make for a test at the =0.01 significance level of 0:=35 versus :35, where is the true mean pressure detected by the pump?

A. Because the null value of 35 is captured by the 99% confidence interval, we would fail to reject 0:=35 at the =0.01 significance level.

B. Because the null value of 35 is not captured by the 99% confidence interval, we would reject 0:=35 at the =0.01 significance level.

C. Because the null value of 35 is not captured by the 99% confidence interval, we would fail to reject 0:=35 at the =0.01 significance level.

D. Because the null value of 35 is captured by the 99% confidence interval, we would reject 0:=35 at the =0.01significance level.