Answer:
P=a+b+c
the given triangle using the Law of Sines. Round lengths to the nearest tenth and angle measurements to the nearest degree.
A) The probability the golfer got zero or one hole-in-one during a single game is between 10.01% and 11.38%.
B) The probability the golfer got exactly two holes-in-one during a single game is 8.57%.
C) The probability the golfer got six holes-in-one during a single game is close to 0%.
<h2 /><h2><u>How to determine probabilities</u></h2>
Since a miniature golf player sinks a hole-in-one about 12% of the time on any given hole and is going to play 8 games at 18 holes each, to determine A) what is the probability the golfer got zero or one hole -in-one during a single game, B) what is the probability the golfer got exactly two holes-in-one during a single game, and C) what is the probability the golfer got six holes-in-one during a single game , the following calculations must be performed:
- 1 - 0.12 = 0.88
- 0.88 ^ 17 = 0.1138
- 0.88 ^ 18 = 0.1001
Therefore, the probability the golfer got zero or one hole-in-one during a single game is between 10.01% and 11.38%.
- 0.88 ^ 18 - 0.12 ^ 2 = X
- 0.0857 = X
Therefore, the probability the golfer got exactly two holes-in-one during a single game is 8.57%.
- 0.12 ^ 6 x 0.88 ^ 12 = X
- 0.0000000001 = X
Therefore, the probability the golfer got six holes-in-one during a single game is close to 0%.
Learn more about probabilities in brainly.com/question/25273534
Answer:
They are SIMILAR triangles
Step-by-step explanation:
Given triangles MNL and FHG with two of their angles to be 51° and 36° respectively. Their third angle is expressed as:
180°-(51°+36°)
= 180°-87°
= 93°
Their third angle is 93°
Since both triangles have the same angles in them, both triangles are considered as similar triangle even though the value of their sides are different due to angle differences in both.
Note that individual triangles are scalene triangles since their angles are not the same but the both triangles are similar triangles based on their relationship.
Answer:
An example of when a continuity correction factor can be used is in finding the number of tails in 50 tosses of a coin within a given range .
and continuity correction factor is used when a continuous probability distribution is used on a discrete probability distribution
Step-by-step explanation:
An example of when a continuity correction factor can be used is in finding the number of tails in 50 tosses of a coin within a given range .
continuity correction factor is used when a continuous probability distribution is used on a discrete probability distribution, continuity correction factor creates an adjustment on a discrete distribution while using a continuous distribution
