Find the slope between: (1,-2) (2,-2)
1 answer:
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Answer:
Step-by-step explanation:
Answer:
There are a 25% probability that Christine fails the course.
Step-by-step explanation:
We have these following probabilities:
A 50% probability that Christine finds a tutor.
With a tutor, she has a 10% probability of failling.
A 50% probability that Christine does not find a tutor.
Without a tutor, she has a 40% probability of failing.
Probability that she fails:
10% of 50%(fail with a tutor) plus 40% of 50%(fail without a tutor). So
There are a 25% probability that Christine fails the course.
Answer:
q = ±
Step-by-step explanation:
We are to solve for q in:
16pq² = 25
q² =
= ±
= ±
Answer:
1) the planning value for the population standard deviation is 10,000
2)
a) Margin of error E = 500, n = 1536.64 ≈ 1537
b) Margin of error E = 200, n = 9604
c) Margin of error E = 100, n = 38416
3)
As we can see, sample size corresponding to margin of error of $100 is too large and may not be feasible.
Hence, I will not recommend trying to obtain the $100 margin of error in the present case.
Step-by-step explanation:
Given the data in the question;
1) Planning Value for the population standard deviation will be;
⇒ ( 50,000 - 10,000 ) / 4
= 40,000 / 4
σ = 10,000
Hence, the planning value for the population standard deviation is 10,000
2) how large a sample should be taken if the desired margin of error is;
we know that, n = [ ( × σ ) / E ]²
given that confidence level = 95%, so = 1.96
Now,
a) Margin of error E = 500
n = [ ( × σ ) / E ]²
n = [ ( 1.96 × 10000 ) / 500 ]²
n = [ 19600 / 500 ]²
n = 1536.64 ≈ 1537
b) Margin of error E = 200
n = [ ( × σ ) / E ]²
n = [ ( 1.96 × 10000 ) / 200 ]²
n = [ 19600 / 200 ]²
n = 9604
c) Margin of error E = 100
n = [ ( × σ ) / E ]²
n = [ ( 1.96 × 10000 ) / 100 ]²
n = [ 19600 / 100 ]²
n = 38416
3) Would you recommend trying to obtain the $100 margin of error?
As we can see, sample size corresponding to margin of error of $100 is too large and may not be feasible.
Hence, I will not recommend trying to obtain the $100 margin of error in the present case.