The probability of finding a substandard weld is: p = 5% =
0.05 <span>
We are given that the sample size: n = 300
Using the Poisson Distribution , the average number of welds (m) is:</span>
m = n*p =
m = 300 * 0.05 <span>
m =15 </span>
<span>
The standard deviation of welds (s) is calculated by:</span>
s = sqrt (m)
s = sqrt (15)
s = 3.873
<span>
<span>Assuming normal distribution, the z value corresponding to 30
sub standards is:
z =( X - Mean) / standard deviation
z =(30 - 15) / 3.873
z = 15 / 3.873
z = 3.87</span></span>
<span>
<span>The z value based on the standard normal curves has a maximum
value of 3.49. Beyond that z value of 3.49 would mean exceeding 100%. Therefore
z = 3.87 is not normal and definitely it is unusual to find 30 or more
substandard.</span></span>
Answer:
1, 1.5
Step-by-step explanation:
Use the rational roots theorem. Factor out until you get the maximum simplification.
0.375(x−1)(2x−3)(19x2+15x+9)
However, if you wanted to solve this equation for <em>r</em>, you will get 1, 1.5 using the quartic formula.
Answer:
-13
Step-by-step explanation:
Answer:
Therefore, the final form
p+/-E = 0.666+/-0.333
Step-by-step explanation:
Given:
Confidence interval = 0.333 < p < 0.999
To express the confidence interval in the forn p+/-E, where;
p is the midpoint of the confidence interval
E is the error.
The midpoint of the confidence interval is
p = (0.333+0.999)/2 = 1.332/2
p = 0.666
The error can be calculated using the formula:
Error = interval width/2
E = (0.999-0.333)/2 = 0.666/2
E = 0.333
Therefore, the final form
p+/-E = 0.666+/-0.333
x+2
