Yellowfin Tuna. A marine biologist claims that the mean fork length of yellowfin tuna is different in two zones in the eastern tropical Pacific Ocean. A sample of 26 yellowfin tuna collected in Zone A has a mean fork length of 76.2 cm and a standard deviation of 16.5 cm. A sample of 31 yellowfin tuna collected in Zone B has a mean fork length of 80.8 cm and a standard deviation of 23.4 cm. At a = 0.01, can you support the marine biologist’s claim? Assume the population variances are equal. Using and Interpreting ConceptsTesting the Difference Between Two Means(a) identify the claim and state Họ and Ha, (b) find the critical value(s) and identifythe rejection region(s), (c) find the standardized test statistic t, (d) decide whetherto reject or fail to reject the null hypothesis, and (e) interpret the decision in thecontext of the original claim. Assume the samples are random and independent,and the populations are normally distributed.In Exercises 13–22, 16. Yellowfin Tuna A marine biologist claims that the mean fork length(see figure at the left) of yellowfin tuna is different in two zones in theeastern tropical Pacific Ocean. A sample of 26 yellowfin tuna collected inZone A has a mean fork length of 76.2 centimeters and a standard deviationof 16.5 centimeters. A sample of 31 yellowfin tuna collected in Zone Bhas a mean fork length of 80.8 centimeters and a standard deviation of23.4 centimeters. At a = 0.01, can you support the marine biologist's claim?Assume the population variances are equal. (Adapted from Fishery Bulletin)%3Dthotthemean

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Description: Yellowfin Tuna. A marine biologist claims that the mean fork length of yellowfin tuna is different in two zones in the eastern tropical Pacific Ocean. A sample of 26 yellowfin tuna collected in Zone A has a mean fork length of 76.2 cm and a standard

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MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Yellowfin Tuna. A marine biologist claims that the mean fork length of yellowfin tuna is different in two zones in the eastern tropical Pacific Ocean. A sample of 26 yellowfin tuna collected in Zone A has a mean fork length of 76.2 cm and a standard deviation of 16.5 cm. A sample of 31 yellowfin tuna collected in Zone B has a mean fork length of 80.8 cm and a standard deviation of 23.4 cm. At a = 0.01, can you support the marine biologist’s claim? Assume the population variances are equal.

Using and Interpreting Concepts
Testing the Difference Between Two Means
(a) identify the claim and state Họ and Ha, (b) find the critical value(s) and identify
the rejection region(s), (c) find the standardized test statistic t, (d) decide whether
to reject or fail to reject the null hypothesis, and (e) interpret the decision in the
context of the original claim. Assume the samples are random and independent,
and the populations are normally distributed.
In Exercises 13–22,

16. Yellowfin Tuna A marine biologist claims that the mean fork length
(see figure at the left) of yellowfin tuna is different in two zones in the
eastern tropical Pacific Ocean. A sample of 26 yellowfin tuna collected in
Zone A has a mean fork length of 76.2 centimeters and a standard deviation
of 16.5 centimeters. A sample of 31 yellowfin tuna collected in Zone B
has a mean fork length of 80.8 centimeters and a standard deviation of
23.4 centimeters. At a = 0.01, can you support the marine biologist's claim?
Assume the population variances are equal. (Adapted from Fishery Bulletin)
%3D
thot
the
mean

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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