Well, for
her questionnaire she could use and create questions or queries that are
obviously related to her hypothesis or study.
These
could be done in a likert type of scale.
<span><span>
1.
</span>I read most often.
</span>
<span><span>a.
</span>Strongly Agree </span>
<span><span>b.
</span>Agree</span>
<span><span>c.
</span>Disagree </span>
<span><span>d.
</span>Strongly Disagree</span>
<span><span>
2.
</span>When I read my books its takes me 24 hours a day</span>
<span><span>
a.
</span>Strongly Agree </span>
<span><span>b.
</span>Agree</span>
<span><span>c.
</span>Disagree </span>
<span><span>d.
</span>Strongly Disagree</span>
<span><span>
3.
</span>When I start reading I can’t stop</span>
<span><span>
a.
</span>Strongly Agree </span>
<span><span>b.
</span>Agree</span>
<span><span>c.
</span>Disagree </span>
<span><span>d.
</span>Strongly Disagree</span>
Answer:
98.1% chance of being accepted
Step-by-step explanation:
Given:
sample size,n=56
acceptance condition= at most 2 batteries do not meet specifications
shipment size=7000
battery percentage in shipment that do not meet specification= 1%
Applying binomial distribution
<h3>P(x)=∑ᵇₐ=₀ (n!/a!(n-a)!)p^a (1-p)^(n-a)</h3>
In this formula, a is the acceptable number of defectives;
n is the sample size;
p is the fraction of defectives in the population.
Now putting the value
a= 2
n=56
p=0.01


=0.56960+0.32219+0.08949
After summation, we get 0.981 i.e. a 98.1% chance of being accepted. As this is such a high chance, we can expect many of the shipments like this to be accepted!
Answer:
-7
Step-by-step explanation:
(7/8)(-16)(-7)(-1/4)
(7/8)(-1/4)(-16)(-7)
(-1/16)(112)
-7