Answer:
21
Step-by-step explanation:
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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The answer would be <span><span>f<span>−1</span></span><span>(x)</span></span>=<span>√<span>36+x</span></span>,<span>−<span>√<span>36+<span>x. I didn't know it in word form :(</span></span></span></span>
La formula para sacar la pendiente:
Y2-Y1/X2-X1
Respuesta:
Y2-Y1/X2-X1= -2-(-10)/-1-(-1)
= -2+10/ -1+1= 8
R=8
Espero que te sirva