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vampirchik [111]
2 years ago
10

One household is to be selected at random from a town. ​ ​The probability that ​the household has a cat is 0.20.2 . ​ ​The proba

bility that the household has a dog ​is 0.40.4 . ​ ​The probability that the household has a cat or a dog is 0.50.5 . ​ ​What is ​the probability that the household has a dog, given that the household has a ​cat? ​ ​Show your work on the scratchpad.
Mathematics
1 answer:
dimulka [17.4K]2 years ago
4 0

Answer:

There is a 50% probability that the household has a dog, given that the household has a ​cat.

Step-by-step explanation:

We solve this problem building the Venn's diagram of these probabilities.

I am going to say that:

A is the probability that a household has a cat.

B is the probability that a household has a dog.

We have that:

A = a + (A \cap B)

In which a is the probability that a household has a cat but not a dog and A \cap B is the probability that a household has both a cat and a dog.

By the same logic, we have that:

B = b + (A \cap B)

The probability that the household has a cat or a dog is 0.5

a + b + (A \cap B) = 0.5

The probability that the household has a dog ​is 0.4

B = 0.4

B = b + (A \cap B)

b = 0.4 - (A \cap B)

The probability that ​the household has a cat is 0.2.

A = 0.2

A = a + (A \cap B)

a = 0.2 - (A \cap B)

So

a + b + (A \cap B) = 0.5

0.2 - (A \cap B) + 0.4 - (A \cap B) + (A \cap B) = 0.5

A \cap B = 0.1

What is ​the probability that the household has a dog, given that the household has a ​cat?

20% of the households have a cat, and 10% have both a cat and a dog. So

P = \frac{A \cap B}{A} = {0.1}{0.2} = 0.5

There is a 50% probability that the household has a dog, given that the household has a ​cat.

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Step-by-step explanation:

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Answer:

\Huge \boxed{s+t}

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G (r) = 25 – 3r<br> g(4) =
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A professor thinks that the students in her statistics class this term are less creative than most students at this university.
choli [55]

Answer:

It is not enough evidence to reject null hypothesis. It is not enough evidence to say that mean score is not equal to 35.

Step-by-step explanation:

\mu=35\\n=23\\\=x=33\\s=5\\\alpha=0.1

1. Null and alternative hypothesis

H_{0}:\mu=35\\H_{1}:\mu

2. Significance level

\alpha=0.1\\1-\alpha=0.99

Freedom degrees is given by:

v=n-1\\v=23-1=22

For a sgnificance level of 0,01 and 22 freedom degrees,  t-student distribution value is:

t_{0.01;23}=-2. 5083

3. Test statistic

t=\frac{\=x-\mu}{\frac{s}{\sqrt{n} } }

t=\frac{33-35}{\frac{5}{\sqrt{23} } }

t=-1,918

In this case, we have an one left tailed analysis, it means that null hypothesis is rejected if t

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Conclusion:

It is not enough evidence to reject null hypothesis. It is not enough evidence to say that mean score is not equal to 35.

3 0
3 years ago
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