If it starts with 0.12 it is false.
But if it starts with 0.009 it is true.
Answer:
Step-by-step explanation:
Expected value of the bet =
<h3>
P(you make the correct draw) * 40 + P(you do not make the correct draw) * (-10) = </h3>
(4/52)(4/51)(4/50) * 40 + (1 - (4/52)(4/51)(4/50)) * (-10) =
(64/132600) * 40 + (1 - 64/132600) *(-10) =
64/3315 + (132536/132600) * (-10) =
64/3315 - (132536/13260) =
64/3315 - 33134/3315 =
-33070/3315 =
-9.97586726998 =
-$9.98, rounded to the nearest cent
(i.e., the expected value of the bet is a loss of $9.98)
Answer:
32.064
Step-by-step explanation:
Answer:
68 feet square
Step-by-step explanation:
The rectangle with the maximum area for a given perimeter is a square. The perimeter of a square is 4 times the side length, so the side length of the square area will be ...
(272 ft)/4 = 68 ft
_____
<em>More formally ...</em>
You can let x represent the length of one side. Then the length of the other side for the given perimeter will be 136 -x, and the area will be the product ...
area = x(136 -x)
The area function is a quadratic with zeros at x=0 and x=136. The vertex (maximum area) will be at the value of x that is on the line of symmetry between these points, at their midpoint: x = (0 +136)/2 = 68. This value of x makes the rectangle a square.
Answer:
And we can find this probability using the normal standard distribution or excel and we got:
Step-by-step explanation:
For this case we assume the following complete question: "The pucks used by the National Hockey League for ice hockey must weigh between 5.5 and 6 ounces. Suppose the weights of pucks produced at a factory are normally distributed with a mean of 5.86 ounces and a standard deviation of 0.13ounces. What percentage of the pucks produced at this factory cannot be used by the National Hockey League? Round your answer to two decimal places.
"
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the normal standard distribution or excel and we got: