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:
Yes, the triangles are simirar with a scale factor of 3/2.
Step-by-step explanation:
We find the scale factor by dividing corresponding sides:
12/8=3/2
18/12=3/2
24/16=3/2
Answer:
y = x-2
Step-by-step explanation:
y = mx + b as an equation
m = slope
slope = (change in y) / (change in x) = (y₂-y₁)/(x₂-x₁) = (y₁-y₂)/(x₁-x₂) = (2-(-2))/(4-0) = 4/4 = 1
y = 1*x + b
plug a value in, e.g. (0, -2)
-2 = 1 * 0 + b
-2 = b
our equation is thus
y = x - 2
Answer:
（-1,-1）（2,0）（4,-20）
Step-by-step explanation:
（-1,-1） = -5 › -6 √
（0,-9） = -9 › -6 ×
（2,0） = 8 › -6 √
（-3,6） = -6 › -6 ×
（4,20） = -4 › -6 √
