The question is incomplete. Here is the complete question:
Samir is an expert marksman. When he takes aim at a particular target on the shooting range, there is a 0.95 probability that he will hit it. One day, Samir decides to attempt to hit 10 such targets in a row.
Assuming that Samir is equally likely to hit each of the 10 targets, what is the probability that he will miss at least one of them?
Answer:
40.13%
Step-by-step explanation:
Let 'A' be the event of not missing a target in 10 attempts.
Therefore, the complement of event 'A' is 
Now, Samir is equally likely to hit each of the 10 targets. Therefore, probability of hitting each target each time is same and equal to 0.95.
Now, 
We know that the sum of probability of an event and its complement is 1.
So, 
Therefore, the probability of missing a target at least once in 10 attempts is 40.13%.
Let s represent number of shirts and h represent number of hats.
We have been given that the organizers of a talent show have budgeted $1800 to buy souvenir clothing to sell at the event. They can buy shirts for $10 each and hats for $8 each.
The cost of s shirts would be 
and cost of h hats would be 
. The cost of s shirts and h hats should be less than or equal to 1800. We can represent this information in an inequality as:
We are also told that organizers plan to buy at least 5 times as many shirts as hats. This means that number of shirts should be greater than or equal to 5 times hats. We can represent this information in an inequality as:
Therefore, the second inequality should be and option C is the correct choice.
Answer:
54.74 ounces of tomatoes mark need.
Step-by-step explanation:
Given : Mark has three 
oz cans and five 
oz cans.
To find : How many ounces of tomatoes does Mark need?
Solution :
Mark has three oz cans.
i.e. 
Mark has five oz cans.
i.e. 
Total ounces of tomatoes does Mark need is
Therefore, 54.74 ounces of tomatoes mark need.
Answer:
with 0.10 level of significance the P-VALUE that would be used in the hypothesis claim is 0.05%
Step-by-step explanation:
In hypothesis testing in statistics, we can say that the p-value is a probability of obtaining test results when we assume that the null hypothesis is correct.
The p-value is the probability that the null hypothesis is true.
A p-value less than or equals to 0.05 is statistically significant. It shows strong evidence against the null hypothesis, meaning there is less than a 5% probability the null is correct and clearly we can say that the results are random.
