A test (Test A) was developed as a possible replacement for an old stat test (Test B). An stat test claimed that mean time to finishe the new test A was more than the mean time to finish an old test B. The summary data for completion time (in minutes) are as follows.Test A : n=7, X bar=158 minutes, S2=165 minutesTest B : n=11 X bar=152 minutes, S2=33 minutesEstimate of standard error=16P=value: Use t-distribution, tp-value is equal to 0.1307 for one tailed test. P-value 0.1307> significance level a=0.10, fail 2 reject. So there is not enough evidence to support the claim that mean time to complete the new test A is more than the meantime to complete old test B.

Given: Test A : n1=7, x1¯=158 minutes, s12=165 minutes Test B : n2=11 x¯2 bar=152 minutes, s22=33…

Answered: An stat test claimed that mean time…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A test (Test A) was developed as a possible replacement for an old stat test (Test B). An stat test claimed that mean time to finishe the new test A was more than the mean time to finish an old test B. The summary data for completion time (in minutes) are as follows.

Test A : n=7, X bar=158 minutes, S²=165 minutes

Test B : n=11 X bar=152 minutes, S²=33 minutes

Estimate of standard error=16

P=value: Use t-distribution, tp-value is equal to 0.1307 for one tailed test. P-value 0.1307> significance level a=0.10, fail 2 reject. So there is not enough evidence to support the claim that mean time to complete the new test A is more than the meantime to complete old test B.

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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