Answer:
Explanation:
This is a test of 2 population proportions. Let 1 and 2 be the subscript for metal parts not shot peened and metal parts shot peened metal parts. The population proportions of fractures on metal parts not shot peened and fractures on metal parts shot peened would be p1 and p2
p1 - p2 = difference in the proportion of fractures on not shot peened and shot peened metal parts.
The null hypothesis is
H0 : p1 = p2
p1 - p2 = 0
The alternative hypothesis is
H1 : p1 > p2
p1 - p2 > 0
it is a right tailed test
Sample proportion = x/n
Where
x represents number of success(number of fractures)
n represents number of samples
For metal parts not shot peened,
x1 = 7
n1 = 35
p1 = 7/35 = 0.2
For metal parts shot peened,
x2 = 3
n2 = 40
p2 = 3/40 = 0.075
The pooled proportion, pc is
pc = (x1 + x2)/(n1 + n2)
pc = (7 + 3)/(35 + 40) = 0.13
1 - pc = 1 - 0.13 = 0.87
z = (p1 - p2)/√pc(1 - pc)(1/n1 + 1/n2)
z = (0.2 - 0.075)/√(0.13)(0.87)(1/35 + 1/40) = - 0.031/0.07783911979
z = 1.61
Since it is a right tailed test, we would find the p value for the area to the right of the z score. From the normal distribution table,
p value = 1 - 0.9463 = 0.0537
Let us assume a significance level of 0.05
Since 0.05 < 0.0537, we would accept the null hypothesis
Therefore, we can conclude that shot peening does not reduce the probability that a part will fracture when put into use.