WALKINGRUNNINGMean7.1818181827.3636364Variance4.5636363646.4545455Observations1111Pooled Variance5.509090909 Hypothesized Mean Difference0 df20 t Stat-0.181668105 P(T<=t) one-tail0.428835886 t Critical one-tail1.724718243 P(T<=t) two-tail0.857671772 t Critical two-tail2.085963447 If the t-Stat value is less than the t Critical two-tail value I can reject the null, right? I am still a little confused on what a few numbers represent.

Name: WALKINGRUNNINGMean7.1818181827.3636364Variance4.5636363646.4545455Obse
Uploaded: 2024-03-20T07:07:12.000Z
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Description: WALKINGRUNNINGMean7.1818181827.3636364Variance4.5636363646.4545455Observations1111Pooled Variance5.509090909 Hypothesized Mean Difference0 df20 t Stat-0.181668105 P(T<=t) one-tail0.428835886 t Critical one-tail1.724718243 P(T<=t) two-tail0.857671772

Introduction: Denote μ1, μ2 as the true population means for walking and running, respectively. The…

Answered: WALKING RUNNING Mean 7.181818182…

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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	WALKING	RUNNING
Mean	7.181818182	7.3636364
Variance	4.563636364	6.4545455
Observations	11	11
Pooled Variance	5.509090909
Hypothesized Mean Difference	0
df	20
t Stat	-0.181668105
P(T<=t) one-tail	0.428835886
t Critical one-tail	1.724718243
P(T<=t) two-tail	0.857671772
t Critical two-tail	2.085963447

If the t-Stat value is less than the t Critical two-tail value I can reject the null, right? I am still a little confused on what a few numbers represent.

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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