Listed below are systolic blood pressure measurements (mm Hg) taken from the right and left arms of the same woman. Assume that the paired sample data is a simple random sample and that the differences have a distribution that is approximately normal. Use a 0.01 significance level to test for a difference between the measurements from the two arms. What can be concluded? Right arm 142 143 123 133 139 Left arm 172 159 190 152 151 In this example, μd is the mean value of the differences d for the population of all pairs of data, where each individual difference d is defined as the measurement from the right arm minus the measurement from the left arm. What are the null and alternative hypotheses for the hypothesis test? A. H0: μd=0 H1: μd≠0 B. H0: μd≠0 H1: μd=0 C. H0: μd=0 H1: μd<0 D. H0: μd≠0 H1: μd>0 Identify the test statistic. t= nothing (Round to two decimal places as needed.) Identify the P-value. P-value= nothing (Round to three decimal places as needed.) What is the conclusion based on the hypothesis test? Since the P-value is ▼ less greater than the significance level, ▼ reject fail to reject the null hypothesis. There ▼ is is not sufficient evidence to support the claim of a difference in measurements between the two arms.

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Description: Listed below are systolic blood pressure measurements (mm Hg) taken from the right and left arms of the same woman. Assume that the paired sample data is a simple random sample and that the differences have a distribution that is approximately norma

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Listed below are systolic blood pressure measurements (mm Hg) taken from the right and left arms of the same woman. Assume that the paired sample data is a simple random sample and that the differences have a distribution that is approximately normal. Use a

0.01

significance level to test for a difference between the measurements from the two arms. What can be concluded?

Right arm	142	143	123	133	139
Left arm	172	159	190	152	151

In this example,

μd

is the mean value of the differences d for the population of all pairs of data, where each individual difference d is defined as the measurement from the right arm minus the measurement from the left arm. What are the null and alternative hypotheses for the hypothesis test?

H0:

μd=0

H1:

μd≠0

H0:

μd≠0

H1:

μd=0

H0:

μd=0

H1:

μd<0

H0:

μd≠0

H1:

μd>0

Identify the test statistic.

nothing

(Round to two decimal places as needed.)

Identify the P-value.

P-value=

nothing

(Round to three decimal places as needed.)

What is the conclusion based on the hypothesis test?

Since the P-value is

▼

less

greater

than the significance level,

▼

reject

fail to reject

the null hypothesis. There

▼

is not

sufficient evidence to support the claim of a difference in measurements between the two arms.

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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