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garri49 [273]
3 years ago
8

A marine biologist will collect data regarding the length and weight of each of 50 trout caught and released at five different l

ocations in a given lake. Which type of visual representation would BEST represent the marine biologist’s data?
a bar graph comparing the largest trout caught at each of the five locations

a scale drawing of all trout caught regardless of location

a circle graph comparing the number of trout caught at each of the five locations

a scatterplot comparing the length and weight of each trout regardless of location
Mathematics
1 answer:
Vesnalui [34]3 years ago
3 0
I think that the best visual representation that the marine biologist would use is utilising a bar graph. A bar graph is composed of bars residing in a coordinate plane. In addition to that, the visual representation would most likely be used since the average weight and length of each trout coming from 5 different locations is compared.
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A machine, when working properly, produces 5% or less defective items. Whenever the machine produces significantly greater than
vovikov84 [41]

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The pvalue of the test is 0.0007 < 0.01, which means that we reject the null hypothesis and accept the alternate hypothesis that the percentage of defective items produced by this machine is greater than 5%.

Step-by-step explanation:

A machine, when working properly, produces 5% or less defective items.

This means that the null hypothesis is:

H_0: p \leq 0.05

Test if the percentage of defective items produced by this machine is greater than 5%.

This means that the alternate hypothesis is:

H_a: p > 0.05

The test statistic is:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the value tested at the null hypothesis, \sigma is the standard deviation and n is the size of the sample.

0.05 is tested at the null hypothesis:

This means that \mu = 0.05, \sigma = \sqrt{0.05*0.95}

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This means that n = 300, X = \frac{27}{300} = 0.09

Value of the test statistic:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

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Testing if the mean is greater than a value, which means that the pvalue of the test is 1 subtracted by the pvalue of Z = 3.18, which is the probability of a finding a sample proportion of 0.09 or higher.

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The pvalue of the test is 0.0007 < 0.01, which means that we reject the null hypothesis and accept the alternate hypothesis that the percentage of defective items produced by this machine is greater than 5%.

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