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Mariulka [41]
3 years ago
10

there are only red counters and blue counters in a bag. Jim takes at random a counter from a bag. the probability that the count

er is red is 0.45 Jim puts the counter back into the bag. Molly takes at random a counter from the bag. She puts the counter back in the bag. What is the probability that Jim and Molly take counters of different colours? Give your answer as a decimal
Mathematics
1 answer:
KengaRu [80]3 years ago
5 0

Answer:

0.495 probability that Jim and Molly take counters of different colours

Step-by-step explanation:

For each trial, there are only two possible outcomes. Either a blue counter is picked, or a red counter is picked. The counter is put back in the bag after it is taken, which means that we can use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

The probability that the counter is red is 0.45

This means that p = 0.45

Jim taken a counter, then Molly:

Two trials, so n = 2

What is the probability that Jim and Molly take counters of different colours?

One red and one blue. So this is P(X = 1).

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 1) = C_{2,1}.(0.45)^{1}.(0.55)^{1} = 0.495

0.495 probability that Jim and Molly take counters of different colours

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Answer:

1. The population of interest on this case is people who felt fully engaged with their mortgage provider

2. On this case the sample size is 1627 the number of people sample selected.

3. ME=1.96\sqrt{\frac{0.22 (1-0.22)}{1627}}=0.0201    

4. The 95% confidence interval would be given (0.1999;0.2401).  

5. We are confident 95% that the true proportion of proportion is between 0.1999 and 0.2401.

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

The margin of error is the range of values below and above the sample statistic in a confidence interval.  

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

The population proportion have the following distribution

p \sim N(p,\sqrt{\frac{p(1-p)}{n}})

1. What is the population?

The population of interest on this case is people who felt fully engaged with their mortgage provider

2. What is the sample size?

On this case the sample size is 1627 the number of people sample selected.

3. What is the 95% margin of error?

In order to find the critical value we need to take in count that we are finding the interval for a proportion, so on this case we need to use the z distribution. Since our interval is at 95% of confidence, our significance level would be given by \alpha=1-0.95=0.05 and \alpha/2 =0.025. And the critical value would be given by:

z_{\alpha/2}=-1.96, z_{1-\alpha/2}=1.96

The margin of error for the proportion interval is given by this formula:  

ME=z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}    (a)  

If we replace we got:

ME=1.96\sqrt{\frac{0.22 (1-0.22)}{1627}}=0.0201    

4. What is the 95% confidence interval?

The confidence interval would be given by this formula  

\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}  

For the 95% confidence interval the value of \alpha=1-0.95=0.05 and \alpha/2=0.025, with that value we can find the quantile required for the interval in the normal standard distribution.  

z_{\alpha/2}=1.96  

And replacing into the confidence interval formula we got:  

0.22 - 1.96 \sqrt{\frac{0.22(1-0.22)}{1627}}=0.1999  

0.22 + 1.96 \sqrt{\frac{0.22(1-0.22)}{1627}}=0.2401  

And the 95% confidence interval would be given (0.1999;0.2401).  

5. Express your answer to 4 in a meaningful sentence.

We can conclude this:

We are confident 95% that the true proportion of proportion is between 0.1999 and 0.2401.

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