: <p>

Car 1    Car 2    Car 3   Car 4   Car 5    Car 6  <p>

Brand A    125      64       100      38       96      112 <p>

Brand B    131      65       103      37       102     115 <p>

(For instance, after Car 1 was outfitted with 4 new brand A tires
and then driven for one month, the total wear on the 4 tires was
125/1000th of an inch; after it was driven for one month with new
brand B tires, the total wear on the 4 tires was 131/1000th of an
inch.)  Let the null hypothesis be that tires of brand A and
tires of brand B wear about equally, and the alternative
hypothesis be that tires of brand B are longer-wearing.  Assume
that the six differences in tire wear (like 131 - 125 = 6 and 37
-38 = -1) are a random sample from a large collection of such
differences whose histogram follows the normal curve. If you test
the null hypothesis against the alternative, the P-value should
turn out to be  <p>

a. less than or equal to .05%  <p>

b. bigger than .05%, but less than or equal to 2.5%  <p>

c. bigger than 2.5%, but less than or equal to 5%  <p>

d. bigger than 5%, but less than or equal to 10%  <p>

e. bigger than 10%