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aleksley [76]
4 years ago
15

The sum of three consecutive odd integers is -129. lost the numbers from smallest to largest.

Mathematics
1 answer:
frozen [14]4 years ago
8 0

Answer:

15ndndndbdbdbdbbdbdbdd

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The two numbers in between which the lower quartile value given by the attached boxplot falls are 1.5 and 2.5 respectively.

  • The lower quartile means the 25th percentile or lower \frac{1}{4}th of the distribution

  • From a boxplot, the lower quartile is the point marked by the starting point of the box.

  • The Lower quartile of the distribution represented by the boxplot is 2

  • The values which bounds the lower quartile value to the left and right are 1.5 and 2.5 respectively.

Therefore, two numbers in between which the lower quartile value falls are 1.5 and 2.5

Learn more :brainly.com/question/24582786

6 0
3 years ago
Suppose 462 of 500 randomly selected college students said they would be embarrassed to truthfully admit they could not read at
ANEK [815]

Answer:

We conclude that there is a significant difference in the proportion of all college students who would be embarrassed by these two admissions.

Step-by-step explanation:

We are given that 462 of 500 randomly selected college students said they would be embarrassed to truthfully admit they could not read at a fourth grade level.

Further suppose 135 of 500 randomly selected college students said they would be embarrassed to truthfully admit they could not "do math" at a fourth grade level (like fractions).

<em>Let </em>p_1<em> = proportion of college students who would be embarrassed to truthfully admit they could not read at a fourth grade level.</em>

p_2<em> = proportion of college students who would be embarrassed to truthfully admit they could not "do math" at a fourth grade level.</em>

So, Null Hypothesis, H_0 : p_1-p_2 = 0  or  p_1= p_2     {means that there is not any significant difference in the proportion of all college students who would be embarrassed by these two admissions}

Alternate Hypothesis, H_A : p_1-p_2 \neq 0  or  p_1\neq p_2     {means that there is a significant difference in the proportion of all college students who would be embarrassed by these two admissions}

The test statistics that would be used here <u>Two-sample z proportion</u> <u>statistics</u>;

                       T.S. =  \frac{(\hat p_1-\hat p_2)-(p_1-p_2)}{\sqrt{\frac{\hat p_1(1-\hat p_1)}{n_1}+\frac{\hat p_2(1-\hat p_2)}{n_2}  } }  ~ N(0,1)

where, \hat p_1 = sample proportion of college students who would be embarrassed to admit they could not read at a fourth grade level = \frac{462}{500} = 0.924

\hat p_2 = sample proportion of college students who would be embarrassed to admit they could not "do math" at a fourth grade level = \frac{135}{500} = 0.27

n_1 = sample of college students = 500

n_2 = sample of college students = 500

So, <em><u>test statistics</u></em>  =  \frac{(0.924-0.27)-(0)}{\sqrt{\frac{0.924(1-0.924)}{500}+\frac{0.27(1-0.27)}{500}  } }

                              =  28.28

The value of z test statistics is 28.28.

<u>Also, P-value of the test statistics is given by;</u>

          P-value = P(Z > 28.28) = Less than 0.0005%

<u></u>

<u>Now, at 0.10 significance level the z table gives critical values of -1.645 and 1.645 for two-tailed test.</u>

Since our test statistics doesn't lie within the range of critical values of z, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u>we reject our null hypothesis</u>.

Therefore, we conclude that there is a significant difference in the proportion of all college students who would be embarrassed by these two admissions.

5 0
4 years ago
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