When doing a t-test comparing two means, the null hypothesis is always that . There is no statistically significant difference between the two means. There is a statistically significant difference between the two means.

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Description: When doing a t-test comparing two means, the null hypothesis is always that . There is no statistically significant difference between the two means. There is a statistically significant difference between the two means

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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When doing a t-test comparing two means, the null hypothesis is always that .

		There is no statistically significant difference between the two means.
		There is a statistically significant difference between the two means.

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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For a t-test comparing two means- The two independent samples application with a continuous outcome, the parameter of interest in the test of hypothesis is the difference in population means, μ₁-μ₂.

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