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Lemur [1.5K]
3 years ago
9

A home pregnancy test is not always accurate. suppose the probability that the test indicates that a woman is pregnant when she

actually is not is 0.02, and the probability the test indicates that a woman is not pregnant when she really is, is 0.03. assume that the probability that a woman who takes the test is actually pregnant is 0.7. what is the probability that a woman is pregnant if the test yields a not pregnant result?
Mathematics
1 answer:
Gnom [1K]3 years ago
4 0
Set Events:
T=tests positive~T=tests negativeP=subject is pregnant~P=subject is not pregnant
We are givenP(T n ~P)=0.02P(~T n P)=0.03P(P)=0.7
recall by definition of conditional probabilityP(A|B)=P(A n B)/P(B)

Need to find P(P|~T)
First step: make a contingency diagram of probabilities (intersection, n)
          P       ~P       sum 
T       0.67   0.02     0.69=P(T) 
~T     0.03   0.28     0.31=P(~T) 
sum   0.70  0.30     1.00
      =P(P)  =P(~P)

therefore
P(P|~T)=P(P n ~T)/P(~T)=0.03/0.31   [ both read off the contingency table ]
=0.0968

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Erika worked 14 hours last week and 20 hours this week. If she earns $9 per hour, how much did she earn during these two weeks?
ozzi

we know that

Erika earns \$9 per hour

so

By proportion

Find how much she earn during the total hours of two weeks

The total hours of two weeks is equal to

14+20=34\ hours

\frac{9}{1} \frac{\$}{hour} =\frac{x}{34} \frac{\$}{hours} \\ \\x=34*9 \\ \\x=\$306

therefore

<u>the answer is</u>

\$306

4 0
3 years ago
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An advertisement for a popular weight-loss clinic suggests that participants in its new diet program lose, on average, more than
Sedbober [7]

Testing the hypothesis, it is found that:

a)

The null hypothesis is: H_0: \mu \leq 10

The alternative hypothesis is: H_1: \mu > 10

b)

The critical value is: t_c = 1.74

The decision rule is:

  • If t < 1.74, we <u>do not reject</u> the null hypothesis.
  • If t > 1.74, we <u>reject</u> the null hypothesis.

c)

Since t = 1.41 < 1.74, we <u>do not reject the null hypothesis</u>, that is, it cannot be concluded that the mean weight loss is of more than 10 pounds.

Item a:

At the null hypothesis, it is tested if the mean loss is of <u>at most 10 pounds</u>, that is:

H_0: \mu \leq 10

At the alternative hypothesis, it is tested if the mean loss is of <u>more than 10 pounds</u>, that is:

H_1: \mu > 10

Item b:

We are having a right-tailed test, as we are testing if the mean is more than a value, with a <u>significance level of 0.05</u> and 18 - 1 = <u>17 df.</u>

Hence, using a calculator for the t-distribution, the critical value is: t_c = 1.74.

Hence, the decision rule is:

  • If t < 1.74, we <u>do not reject</u> the null hypothesis.
  • If t > 1.74, we <u>reject</u> the null hypothesis.

Item c:

We have the <u>standard deviation for the sample</u>, hence the t-distribution is used. The test statistic is given by:

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

The parameters are:

  • \overline{x} is the sample mean.
  • \mu is the value tested at the null hypothesis.
  • s is the standard deviation of the sample.
  • n is the sample size.

For this problem, we have that:

\overline{x} = 10.8, \mu = 10, s = 2.4, n = 18

Thus, the value of the test statistic is:

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

t = \frac{10.8 - 10}{\frac{2.4}{\sqrt{18}}}

t = 1.41

Since t = 1.41 < 1.74, we <u>do not reject the null hypothesis</u>, that is, it cannot be concluded that the mean weight loss is of more than 10 pounds.

A similar problem is given at brainly.com/question/25147864

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bija089 [108]

Answer:

Step-by-step explanation:

-5t ≥ 70

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