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vaieri [72.5K]
3 years ago
12

A 99% confidence interval for the difference between two proportions was estimated at 0.11, 0.39. Based on this, we can conclude

that the two population proportions are equal.
Mathematics
1 answer:
sladkih [1.3K]3 years ago
4 0

Answer:

\hat p_1 -\hat p_2 \pm z_{\alpha/2} SE

And for this case the confidence interval is given by:

0.11 \leq p_1 -p_2 \leq 0.39

Since the confidenc einterval not contains the value 0 we can conclude that we have significant difference between the two population proportion of interest 1% of significance given. So then we can't conclude that the two proportions are equal

Step-by-step explanation:

Let p1 and p2 the population proportions of interest and let \hat p_1 and \hat p_2 the estimators for the proportions we know that the confidence interval for the difference of proportions is given by this formula:

\hat p_1 -\hat p_2 \pm z_{\alpha/2} SE

And for this case the confidence interval is given by:

0.11 \leq p_1 -p_2 \leq 0.39

Since the confidence interval not contains the value 0 we can conclude that we have significant difference between the two population proportion of interest 1% of significance given. So then we can't conclude that the two proportions are equal

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Evaluate AB for A = 5, B =-2, C = 4 and D = -6.<br> 5/12<br> -5/12<br> -3/2<br> 3/2
Nezavi [6.7K]

Answer:

AB = -10

Im confused is this what you wanted?

5 0
3 years ago
A) How many cups of energy drink does Jerome need to make?
Margaret [11]

Answer: You should take the 22÷8 and take 22÷3 and see what you get if that doesn’t help create a table chart or graph

Step-by-step explanation: I said divide 22 by 8 and 22 divide by 3 because that should give you the number that you need for each one

4 0
3 years ago
Suppose that the population mean for income is $50,000, while the population standard deviation is 25,000. If we select a random
Fudgin [204]

Answer:

Probability that the sample will have a mean that is greater than $52,000 is 0.0057.

Step-by-step explanation:

We are given that the population mean for income is $50,000, while the population standard deviation is 25,000.

We select a random sample of 1,000 people.

<em>Let </em>\bar X<em> = sample mean</em>

The z-score probability distribution for sample mean is given by;

               Z = \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }  ~ N(0,1)

where, \mu = population mean = $50,000

            \sigma = population standard deviation = $25,000

            n = sample of people = 1,000

The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X.

So, probability that the sample will have a mean that is greater than $52,000 is given by = P(\bar X > $52,000)

  P(\bar X > $52,000) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{52,000-50,000}{\frac{25,000}{\sqrt{1,000} } } ) = P(Z > 2.53) = 1 - P(Z \leq 2.53)

                                                                    = 1 - 0.9943 = 0.0057

<em>Now, in the z table the P(Z </em>\leq<em> x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 2.53 in the z table which has an area of 0.9943.</em>

Therefore, probability that the sample will have a mean that is greater than $52,000 is 0.0057.

5 0
3 years ago
A state offers two lottery games, WinOne and PlayBall. Both games cost $2 per ticket.
uysha [10]
In this question, both tickets cost 2$ per ticket.
The answer to this question would be: $0

In WinOne scenario, you need to match a ticket that has to pick from A-J(10 possibilities) and 0-9 (10 possibilities). The chance to win would be: 1/10* 1/10= 1/100

The expected value must be:
E= chance to win * win amount - ticket price
E= 1//100*$200 - $2= $2-$2= 0
8 0
3 years ago
The waiting time, in hours, between successive speeders spotted by a radar unit is a continuous ran- dom variable with a cumulat
enyata [817]

Answer: 0.5507

Step-by-step explanation:

Given : The waiting time, in hours, between successive speeders spotted by a radar unit is a continuous random variable X with a cumulative distribution function

F(x)= \begin{cases}0,& x

Since , the waiting time is in hours , then we can write 12 minutes as \dfrac{12}{60} hour i.e.0.2 hour.

Now, the probability of waiting fewer than 12 minutes between successive speeders is given by :-

P(X

Hence, the required probability = 0.5507

4 0
3 years ago
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