Suppose you're testing H0:p=0.62 {"version":"1.1","math":"H_0:p=0.62 "} against Ha:p≠0.62 {"version":"1.1","math":"H_a:p\neq 0.62"} and you have calculated the test statistic to be z=1.334 {"version":"1.1","math":"z = 1.334"}. The area to the right of z=1.334 {"version":"1.1","math":"z = 1.334"} (under the standard normal density curve) is 0.091. What is the P-value of your hypothesis test?

113.42

i hope that is right.

step-by-step explanation:

the answer is a. 72. but i cant answer with less than 20 characters so here's some random text talking about it.

a) 40 more; b) old factory:   10%, new factory:   16%; c) week 4

explanation:

a) at week 0, we see in the graph that the new factory produces 190 specialty items.  

using the function, substituting 0 in for w,

this is a difference of 230-190 = 40.

b) the function for the old factory is written in the form f(x) = a(1+r)ˣ, where a is the original amount, x is the amount of time and r is the growth rate.   the equation for the old factory is ; 230 is in place of a and is the original amount; w is the amount of time; which means 1+r = 1.1.   this means that r must be 0.1 or 10%.

for the new factory, we find the percent of increase to find the growth rate; the formula for this is

between the first two points, the amount of change is 220-190 = 30; this gives us

30/190 = 0.158 ≈ 0.16 = 16%

c) at week 0, the old factory has 230 while the new factory has 190.

at week 1, the old factory has 230(1.1) = 253 while the new factory has 220.

at week 2, the old factory has 230(1.1²) = 278.3 while the new factory has 252.

at week 3, the old factory has 230(1.1³) = 306.13 while the new factory has 290.

at week 4, the old factory has 230(1.1⁴) = 336.743 while the new factory has 337.   this is the first week that the new factory surpasses the old.