Z = (X-Mean)/SD
<span>z1 = (165 - 150)/15 = +1 </span>
<span>z2 = (135 - 150)/15 = - 1 </span>
<span>According to the Empirical Rule 68-95-99.7 </span>
<span>Mean +/- 1SD covers 68% of the values </span>
<span>100% - 68% = 32% </span>
<span>The remaining 32% is equally distributed below z = - 1 and z = +1 </span>
<span>32%/2 = 16%
</span>
<span>Therefore,
</span>
<span>a) Number of men weighing more than 165 pounds = 16% of 1000 = 160 </span>
<span>b) Number of men weighing less than 135 pounds = 16% of 1000 = 160</span>
Five times the difference of a number n and forty two is ten more than twice the product of a number x and number y
- Five times: 5 ×
- difference of a number n and forty two: (n - 42)
- is: =
- twice the product of a number x and a number y: 2(xy)
- ten more than: + 10
Rewrite the expression into an equation.
<h3>5(n - 42) = 2(xy) + 10</h3>
Answer:
c
Step-by-step explanation:
Answer:
By the Central Limit Theorem, it is approximately normal with mean 650 and standard deviation 4.
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean 
and standard deviation 
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation 
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
Mean of 650 and a standard deviation of 24.
This means that 
.
Sample of 36:
This means that 
What is the shape of the sampling distribution you would expect to produce?
By the Central Limit Theorem, it is approximately normal with mean 650 and standard deviation 4.
It's 3/4 because the only factor you can divide them both with is 2 and 3 and 4 have noi factors to divide by to make it lower.
