H0 (null hypothesis): μ1 = μ2 = μ3 = μ4 = μ5 (all the population means are equal)H1 (null hypothesis): at least one population mean is different from the restWhere μ1, μ2, μ3, μ4, μ5 are average daily returns (on the stock you are assigned) on MON, TUE, WED, THR, and FRI respectively. Please explain your answer. dow1SA WNP2Total345TotalSourceBetween groupsWithin groupsSummary of g _KOStd. Dev.Mean.00125015-.00138331.00111933.00085789.00165648.0006892.01056199.0109803.01357690080871.01230139.01123165Analysis of VarianceSSdf.000291704.031245802Freq..031537506 250MS47515251504.000072926246 .000127015251Bartlett's test for equal variances: chi2(4).00012615F0.57Prob > F0.6816= 14.0744 Prob>chi2 = 0.007

Given Information: Null Hypothesis H0:μ1=μ2=μ3=μ4=μ5 Alternative Hypothesis H1: at least one…

Answered: H0 (null hypothesis): μ1 = μ2 = μ3 = μ4…

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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H₀(null hypothesis): μ₁ = μ₂ = μ₃ = μ₄ = μ₅ (all the population means are equal)
H₁(null hypothesis): at least one population mean is differentfrom the rest

Where μ₁, μ₂, μ₃, μ₄, μ₅ are average daily returns (on the stock you are assigned) on MON, TUE, WED, THR, and FRI respectively. Please explain your answer.

dow
1
SA WNP
2
Total
3
4
5
Total
Source
Between groups
Within groups
Summary of g _KO
Std. Dev.
Mean
.00125015
-.00138331
.00111933
.00085789
.00165648
.0006892
.01056199
.0109803
.0135769
0080871
.01230139
.01123165
Analysis of Variance
SS
df
.000291704
.031245802
Freq.
.031537506 250
MS
47
51
52
51
50
4
.000072926
246 .000127015
251
Bartlett's test for equal variances: chi2(4)
.00012615
F
0.57
Prob > F
0.6816
= 14.0744 Prob>chi2 = 0.007

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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