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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X = 13.26
here’s a photo with the work if that helps at all :)
Answer:
$64,000
Step-by-step explanation:
Friday, 45 / 9 = 5
So the investment will double 5 times
First time
2,000 (starting investment) × 2 = 4000
Second time
4000 × 2 = 8000
Third time
8000 × 2 = 16000
Fourth time
16000 × 2 = 32000
Fifth and final time
32000 × 2 = 64000
$64,000
Answer:
~
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Step-by-step explanation:
From the question we are told that:
Price of 20TVs per week
Marginal price-demand function 
Generally the The Marginal price function is mathematically given by
Therefore the equation when the demand is 20 TVs per week at $150 per TV

Giving

Therefore the Price when the demand is 100 TVs per week


Answer:
Step-by-step explanation:
We have to remind one of the properties of the limits:
Lim x→a f(x)*g(x) = [Lim x→a f(x)]*[Lim x→a g(x)]
Hence, we evaluate the products of the limits
(a) Lim x→a f(x)*g(x) = 0*0 = 0
(b) Lim x→a f(x)*p(x) = 0*[infinity] = INDETERMINATE
(c) Lim x→a h(x)*p(x) = 1*[infinity] = infinity
(d) Lim x→a p(x)*q(x) = [infinity]*[infinity] = INDETERMINATE