-15x=-4x
We know that adding zero wouldn’t change the value
-15x=-4x+0
Now we can add 4x (since that’s the opposite of the negative sign) to the other side
-11x=0
0 divided by 11 is 0
x=0
Answer: 0.68
Step-by-step explanation:
given data:
ABC market share = 30%
number of customers surveyed = 800
probability that more than 32% prefers ABC
Solution:
32% of 800
= 256 persons
p ( x ≥ 256 )
= 1 - ( 256/800 )
= 1 - 0.32
= 0.68
the probabiliy that more than 32% of those who carried out the survey would prefer ABC brand is 0.68.
It's very easy!
.
First of all, add up all the amounts of all can flavors.
.
What do you think it approximates to?
.
I'd say 245.
.
Now, how much is 30 out of 245?
.
Around 24%.
.
So, what's 245/100? (100 because it is default maximum percentage number)
<span>.
</span>2.45.
.
24 divided by 2.45?
.
Around 9%.
.
Your best guess is 10% or D.
I think this problem gave the data for the radius of earth so that we will know the conversion ratio between statute miles and nautical miles. However, you can simply search that. There are 1.15 statute miles in 1 nautical mile. Hence,
Distance in nautical miles = <span>884884 statute miles * 1 nautical mile/1.15 statute miles
<em>Distance =769,464.35 nautical miles</em></span>
Answer:
There is approximately 17% chance of a person not having a disease if he or she has tested positive.
Step-by-step explanation:
Denote the events as follows:
<em>D</em> = a person has contracted the disease.
+ = a person tests positive
- = a person tests negative
The information provided is:
Compute the missing probabilities as follows:
The Bayes' theorem states that the conditional probability of an event, say <em>A</em> provided that another event <em>B</em> has already occurred is:
Compute the probability that a random selected person does not have the infection if he or she has tested positive as follows:
So, there is approximately 17% chance of a person not having a disease if he or she has tested positive.
As the false negative rate of the test is 1%, this probability is not unusual considering the huge number of test done.
