Collect and summarize data into a test statistic.The sample mean difference =and the standard error of the difference is = Hypothesis TestingAnswer the given problem by following the steps in hypothesis testing.Sample problem: Determine the weight of the students before and during the quarantine.Did the students lose more fat before the quarantine?Weight before quarantine:Weight during quarantine:sample mean == 4.1 kgsample mean = 5.9 kgsample standard deviation = 3.7 kgsample standard deviation = 4.1 kgsample size = n = 47%3Dsample size= n = 42standard error = SEM2 = 3.7/ V47 = 0.540standard error =SEM1 = 4.1/ v42 = 0.633measure of variability = sq root [(0.633)2 +(0.540)2] = 0.83

Name: Collect and summarize data into a test statistic.The sample mean diffe
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Description: Collect and summarize data into a test statistic.The sample mean difference =and the standard error of the difference is = Hypothesis TestingAnswer the given problem by following the steps in hypothesis testing.Sample problem: Determine the weight of

Determine the null and alternative hypotheses. H0: Null Hypothesis: μd =0 ( The students did not…

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MATLAB: An Introduction with Applications

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Author:Amos Gilat

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Collect and summarize data into a test statistic.

The sample mean difference =
and the standard error of the difference is =

Hypothesis Testing
Answer the given problem by following the steps in hypothesis testing.
Sample problem: Determine the weight of the students before and during the quarantine.
Did the students lose more fat before the quarantine?
Weight before quarantine:
Weight during quarantine:
sample mean =
= 4.1 kg
sample mean = 5.9 kg
sample standard deviation = 3.7 kg
sample standard deviation = 4.1 kg
sample size = n = 47
%3D
sample size
= n = 42
standard error = SEM2 = 3.7/ V47 = 0.540
standard error =
SEM1 = 4.1/ v42 = 0.633
measure of variability = sq root [(0.633)2 +
(0.540)2] = 0.83

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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