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Karo-lina-s [1.5K]
2 years ago
7

Which values are outliers? 6. 1, 3. 9, 6. 4, 10. 6, 4. 4, 4. 5, 1. 6, 11. 2, 0. 8, 3. 9, 6. 5 Select Outlier or Not Outlier for

each data point. Data Outlier Not Outlier 0. 8 Outlier – 0. 8 Not Outlier – 0. 8 1. 6 Outlier – 1. 6 Not Outlier – 1. 6 10. 6 Outlier – 10. 6 Not Outlier – 10. 6 11. 2 Outlier – 11. 2 Not Outlier – 11. 2.
Mathematics
1 answer:
Kisachek [45]2 years ago
8 0

Answer:

<em>10 and 11</em>

Step-by-step explanation:

  1. An outlier is a number that is much larger or smaller than the general populous of numbers. For example, if there was a dot plot with dots clustered at 2, 3, and 5, but there was one or two dots around 10, then 10 would be considered an outlier.
  2. Let's put the numbers in order to see easier which numbers are outliers. I will not copy down repeating numbers.
  3. 0, 1, 2, 3, 4, 5, 6, 10, 11.
  4. 10 and 11 are isolated.

If I am incorrect in my reasoning, please let me know so that I can plan better for my future answers. Have an amazing day.

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Fudgin [204]

Answer:

a) The point estimate of the proportion of items returned for the population of

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b) The 95% confidence interval for the proportion of returns at the Houston store = [0.0718 < p < 0.2282].

c) Yes.

We set an hypothesis and construct a test statistics. The test statistics result gives us:

Z calculated  = 2.2545, and this gives us the p-value = 0.0121. We assumed 95% confident interval. Hence, the level of significance (α) = 5%. Conclusively, since the p-value ==> 0.0121 is less than (α) = 5%, the test is significant. Hence, the proportion of returns at the Houston store is significantly different from the returns  for the nation as a whole.

Step-by-step explanation:

a) Point estimate of the proportion = number of returned items/ total items sold = 12/80 = 0.15.

b) By formula of confident interval:

CI(95%) = p ± Z*\sqrt{\frac{p*(1-p)}{n} }  =  0.15 \pm 1.96 *\sqrt{\frac{0.15*(1-0.15)}{80} },

CI(95%) = [0.0718 < p < 0.2282]

c) The hypothesis:

H_{0}: The proportion of returns at the Houston store is not significantly different from the returns  for the nation as a whole.

H_{a}: The proportion of returns at the Houston store is significantly different from the returns  for the nation as a whole.

The test statistics:

Z = \frac{\hat{p} - p_{0}}{\sqrt{\frac{p*(1-p)}{n} }}, where p_{0} is the proportion of nation returns.

Z calculated  = 2.2545, and this gives us the p-value = 0.0121. We assumed 95% confident interval. Hence, the level of significance (α) = 5%. Conclusively, since the p-value ==> 0.0121 is less than (α) = 5%, the test is significant. Hence, the proportion of returns at the Houston store is significantly different from the returns  for the nation as a whole.

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Step-by-step explanation:

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Answer:

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Step-by-step explanation:

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3 years ago
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Answer:

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Kazeer [188]

Answer:

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Step-by-step explanation:

The slope is found using the formula ...

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Point-slope equation:

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