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drek231 [11]
3 years ago
13

Help due today No links

Mathematics
2 answers:
Pavel [41]3 years ago
5 0

Answer:

<h2><em><u>-11</u></em></h2>

Step-by-step explanation:

24 + _________ = 13

<em>(</em><em>Taking</em><em> </em><em>'</em><em>________'</em><em> </em><em>=</em><em> </em><em>'</em><em>x'</em><em>,</em><em> </em><em>then</em><em>)</em>

=> 24 + x = 13

=> x = 13 - 24

=> x = -11

=> <em><u>__________</u></em><em><u> </u></em><em><u>=</u></em><em><u> </u></em><em><u> </u></em><em><u>-11</u></em><em><u> </u></em><em><u>(</u></em><em><u>Ans</u></em><em><u>)</u></em>

Setler [38]3 years ago
4 0

Answer:

-11

Step-by-step explanation:

24 + x = 13

Subtract 24 from each side

24+x-24 = 13-24

x = -11

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) The National Assessment of Educational Progress (NAEP) gave a test of basic arithmetic and the ability to apply it in everyday
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Answer:

a) The standard deviation of this sampling distribution is 2.07.

b) The missing number is 4.14.

c) The 95% confidence interval for the population mean score μ based on this one sample is between 267.86 and 276.14.

Step-by-step explanation:

To solve this question, we need to understand the Empirical Rule and the Central Limit Theorem.

Empirical Rule:

The Empirical Rule states that, for a normally distributed random variable:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviation of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

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.

In this question:

\mu = 272, n = 840, \sigma = 60

(a) If we take many samples, the sample mean x⎯⎯⎯ varies from sample to sample according to a Normal distribution with mean equal to the unknown mean score μ in the population. What is the standard deviation of this sampling distribution?

Using the Central Limit Theorem:

s = \frac{\sigma}{\sqrt{n}} = \frac{60}{\sqrt{840}} = 2.07

The standard deviation of this sampling distribution is 2.07.

(b) According to the 95 part of the 68-95-99.7 rule, 95% of all values of x⎯⎯⎯ fall within _______ on either side of the unknown mean μ. What is the missing number?

Within 2 standard deviations of the mean.

So, 2*2.07 = 4.14

The missing number is 4.14.

(c) What is the 95% confidence interval for the population mean score μ based on this one sample?

Within 4.14 of the mean

272 - 4.14 = 267.86

272 + 4.14 = 276.14

The 95% confidence interval for the population mean score μ based on this one sample is between 267.86 and 276.14.

6 0
3 years ago
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