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oksano4ka [1.4K]
3 years ago
10

Jenna has a dress up for an interview. She has 3 different shoes to choose from and 4 different suits. How many combinations of

outfits does she have?
Mathematics
2 answers:
denis23 [38]3 years ago
8 0
I think 12 different combinations that Jenna would be able to choose from. 
nalin [4]3 years ago
4 0
She has 12 different options. (3x4=12. 4 options for each shoe)
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CAN SOMEONE PLEASE HELP ME
nadya68 [22]
Well it should be 4 hope it is correct
6 0
3 years ago
A pollster believes that 20% of the voters in a certain area favor a bond issue. If 81 voters are randomly sampled from the larg
lbvjy [14]

Answer:

0.3472 = 34.72% probability that the sampled fraction of voters favoring the bond issue will not differ from the true fraction by more than 0.02.

Step-by-step explanation:

To solve this question, we use the normal probability distribution and the central limit theorem.

Normal probability distribution:

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value 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. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem:

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

In this question:

Proportion p = 0.2, sample of n = 81. So

\mu = p = 0.2

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.2*0.8}{81}} = 0.0444

Approximate the probability that the sampled fraction of voters favoring the bond issue will not differ from the true fraction by more than 0.02.

Probability of the sampled proportion being between 0.2 - 0.02 = 0.18 and 0.2 + 0.02 = 0.22, which is the pvalue of Z when X = 0.22 subtracted by the pvalue of Z when X = 0.18. So

X = 0.22

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{0.22 - 0.2}{0.044}

Z = 0.45

Z = 0.45 has a pvalue of 0.6736

X = 0.18

Z = \frac{X - \mu}{s}

Z = \frac{0.18 - 0.2}{0.044}

Z = -0.45

Z = -0.45 has a pvalue of 0.3264

0.6736 - 0.3264 = 0.3472 = 34.72% probability that the sampled fraction of voters favoring the bond issue will not differ from the true fraction by more than 0.02.

7 0
3 years ago
87 is what percent of 66
kozerog [31]
131.818182% and can round to 131.82
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Use GCF and the distributive property to write equivalent
marissa [1.9K]

Answer:

Step-by-step explanation:

Greatest common factor of 6x and 9y is 3.

6x + 9y = 3(2x + 3y)

:::::

Greatest common factor of 3c and 11c is c.

3c + 11c = (3+11)c

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3 years ago
Simplify -4.5+4.2+5.6-7.3
kumpel [21]

Answer:

-2

Step-by-step explanation:

Hope you do well on your assignment!

6 0
3 years ago
Read 2 more answers
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