As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution whenever the sample size is large.
<h3>What is the Central limit theorem?</h3>
- The Central limit theorem says that the normal probability distribution is used to approximate the sampling distribution of the sample proportions and sample means whenever the sample size is large.
- Approximation of the distribution occurs when the sample size is greater than or equal to 30 and n(1 - p) ≥ 5.
Thus, as a rule of thumb, the sampling distribution of the sample proportions can be approximated by a normal probability distribution when the sample size is large and each element is selected independently from the same population.
Learn more about the central limit theorem here:
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Answer:
A
Step-by-step explanation:
We know it cant be -6 as that would be a range and since the circle on the end is hallow it wont be less or equal to rather just less than and the since the next one is 2 and its solid circle it has to be less than or equal too
3x + 4y = 16
-4x - 3y = -19
4( 3x + 4y = 16)
3( -4x - 3y = -19)
Distribute
12x + 16y = 64
-12x - 9y = -57
Now subtract both equations
7y = 7
/7 on both sides
y = 1
Substitute y = 1 in one of the equations.
3x + 4y = 16
3x + 4(1) = 16
-4 on both sides
3x = 12
/3 on both sides
x = 4
Answer:
x = 4
y = 1
