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:
Step-by-step explanation:
Parts of the question are missing.
y = a(x-h)² + k is a vertical parabola.
If a is positive, the parabola opens upwards.
If a is negative, the parabola opens downwards.
The vertex is at (h, k)
<span>C(15,9) * (1/2)^9 * (1/2)^6 = 5005/32768 = .153 approx</span>
First one is : D (6)
Second one is : B (1/3)
Hope this helps!
Please give Brainliest!
Answer:
65 degrees
Step-by-step explanation:
85 + 30 = 115
180 - 115 = 65
Verify:
a + b + c = 180
85 + 30 + 65 = 180
180 = 180
