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Formula review

The Central Limit Theorem for Sums: ∑X ~ N [( n )( μ x ),( n )( σ x )]

Mean for Sums ( ∑X ): ( n )( μ x )

The Central Limit Theorem for Sums z -score and standard deviation for sums: z for the sample mean =  Σ x ( n ) ( μ X ) ( n ) ( σ X )

Standard deviation for Sums ( ∑X ): ( n ) ( σ x )

Use the following information to answer the next four exercises: An unknown distribution has a mean of 80 and a standard deviation of 12. A sample size of 95 is drawn randomly from the population.

Find the probability that the sum of the 95 values is greater than 7,650.

0.3345

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Find the probability that the sum of the 95 values is less than 7,400.

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Find the sum that is two standard deviations above the mean of the sums.

7,833.92

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Find the sum that is 1.5 standard deviations below the mean of the sums.

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Use the following information to answer the next five exercises: The distribution of results from a cholesterol test has a mean of 180 and a standard deviation of 20. A sample size of 40 is drawn randomly.

Find the probability that the sum of the 40 values is greater than 7,500.

0.0089

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Find the probability that the sum of the 40 values is less than 7,000.

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Find the sum that is one standard deviation above the mean of the sums.

7,326.49

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Find the sum that is 1.5 standard deviations below the mean of the sums.

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Find the percentage of sums between 1.5 standard deviations below the mean of the sums and one standard deviation above the mean of the sums.

77.45%

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Use the following information to answer the next six exercises: A researcher measures the amount of sugar in several cans of the same soda. The mean is 39.01 with a standard deviation of 0.5. The researcher randomly selects a sample of 100.

Find the probability that the sum of the 100 values is greater than 3,910.

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Find the probability that the sum of the 100 values is less than 3,900.

0.4207

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Find the probability that the sum of the 100 values falls between the numbers you found in [link] and [link] .

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Find the sum with a z –score of –2.5.

3,888.5

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Find the sum with a z –score of 0.5.

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Find the probability that the sums will fall between the z -scores –2 and 1.

0.8186

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Use the following information to answer the next four exercise: An unknown distribution has a mean 12 and a standard deviation of one. A sample size of 25 is taken. Let X = the object of interest.

What is the mean of ΣX ?

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What is the standard deviation of ΣX ?

5

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What is P ( Σx >290)?

0.9772

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True or False: only the sums of normal distributions are also normal distributions.

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In order for the sums of a distribution to approach a normal distribution, what must be true?

The sample size, n , gets larger.

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What three things must you know about a distribution to find the probability of sums?

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An unknown distribution has a mean of 25 and a standard deviation of six. Let X = one object from this distribution. What is the sample size if the standard deviation of ΣX is 42?

49

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An unknown distribution has a mean of 19 and a standard deviation of 20. Let X = the object of interest. What is the sample size if the mean of ΣX is 15,200?

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Use the following information to answer the next three exercises.
A market researcher analyzes how many electronics devices customers buy in a single purchase. The distribution has a mean of three with a standard deviation of 0.7. She samples 400 customers.

What is the z -score for Σx = 840?

26.00

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What is the z -score for Σx = 1,186?

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What is P ( Σx <1,186)?

0.1587

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Use the following information to answer the next three exercises:
An unkwon distribution has a mean of 100, a standard deviation of 100, and a sample size of 100. Let X = one object of interest.

What is the mean of ΣX ?

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What is the standard deviation of ΣX ?

1,000

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What is P ( Σx >9,000)?

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Source:  OpenStax, Introductory statistics. OpenStax CNX. May 06, 2016 Download for free at http://legacy.cnx.org/content/col11562/1.18
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