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Mama L [17]
3 years ago
13

I don’t know the unit rate to this problem

Mathematics
1 answer:
Ierofanga [76]3 years ago
8 0

Answer:

Since its counting by 2 go between 0 and 2 which is one and go up the blue line so the answer is 10

Step-by-step explanation:

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What is the equation simplified
Lilit [14]

\bf \cfrac{2}{7}(2s+3)\implies \stackrel{\textit{distributing}}{\cfrac{2}{7}\cdot 2s+\cfrac{2}{7}\cdot 3}\implies \cfrac{2\cdot 2}{7}s+\cfrac{2\cdot 3}{7}\implies \cfrac{4}{7}s+\cfrac{6}{7}

4 0
3 years ago
Suppose a continuous probability distribution has an average of μ=35 and a standard deviation of σ=16. Draw 100 times at random
yulyashka [42]

Answer:

To use a Normal distribution to approximate the chance the sum total will be between 3000 and 4000 (inclusive), we use the area from a lower bound of 3000 to an upper bound of 4000 under a Normal curve with its center (average) at 3500 and a spread (standard deviation) of 160 . The estimated probability is 99.82%.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using 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 sums, we have that the mean is \mu*n and the standard deviation is s = \sigma \sqrt{n}

In this problem, we have that:

\mu = 100*35 = 3500, \sigma = \sqrt{100}*16 = 160

This probability is the pvalue of Z when X = 4000 subtracted by the pvalue of Z when X = 3000.

X = 4000

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

By the Central Limit Theorem

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

Z = \frac{4000 - 3500}{160}

Z = 3.13

Z = 3.13 has a pvalue of 0.9991

X = 3000

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

Z = \frac{3000 - 3500}{160}

Z = -3.13

Z = -3.13 has a pvalue of 0.0009

0.9991 - 0.0009 = 0.9982

So the correct answer is:

To use a Normal distribution to approximate the chance the sum total will be between 3000 and 4000 (inclusive), we use the area from a lower bound of 3000 to an upper bound of 4000 under a Normal curve with its center (average) at 3500 and a spread (standard deviation) of 160 . The estimated probability is 99.82%.

5 0
3 years ago
Selma uses a jogging trail that runs through a park near her home. The trail is a loop that is 3/4 of a mile long. On Monday, Se
KIM [24]
(3/4) / (1/6) =
3/4 * 6/1 =
18/4 =
4.5 miles per hr <==
7 0
3 years ago
if i bottle flip a bottle 17 times and there is a ratio of 2 to 3 of it landing how many times will it land
blondinia [14]
The bottle will land about 11 out of the 17 times
hope i helped ( ಥـْـِـِـِـْಥ)
7 0
2 years ago
Which of the following statements is not true about the numbers 7 and -7?
leonid [27]

Answer:

incorrect is They have a sum of -14

4 0
3 years ago
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