An economist wonders if corporate productivity in some countries is more volatile than in other countries. One measure of a company's productivity is annual percentage yield based on total company assets.
A random sample of leading companies in France gave the
following percentage yields based on assets.
4.2 5.1 3.2 3.1
2.2 3.5 2.8 4.4
5.7 3.4 4.1
6.8 2.9 3.2 7.2
6.5 5.0 3.3 2.8
2.5 4.5
Use a calculator to verify that the sample variance is s2 ≈ 2.119
for this sample of French companies.
Another random sample of leading companies in Germany gave the
following percentage yields based on assets.
3.0 3.5 3.7 4.3
5.3 5.5 5.0 5.4
3.2
3.5 3.7 2.6 2.8
3.0 3.0 2.2 4.7
3.2
Use a calculator to verify that s2 ≈ 1.059 for this sample of
German companies.
Test the claim that there is a difference (either way) in the
population variance of percentage yields for leading companies in
France and Germany. Use a 5% level of significance. How could your
test conclusion relate to the economist's question regarding
volatility (data spread) of corporate productivity of large
companies in France compared with companies in Germany?
(a) What is the level of significance?
State the null and alternate hypotheses.
Ho: σ12 = σ22; H1: σ12 > σ22
Ho: σ12 > σ22; H1: σ12 = σ22
Ho: σ22 = σ12; H1: σ22 > σ12
Ho: σ12 = σ22; H1: σ12 ≠ σ22
(b) Find the value of the sample F statistic. (Use 2 decimal
places.)
What are the degrees of freedom?
dfN
dfD
What assumptions are you making about the original
distribution?
The populations follow independent normal distributions. We have
random samples from each population.
The populations follow independent normal distributions.
The populations follow independent chi-square distributions. We
have random samples from each population.
The populations follow dependent normal distributions. We have
random samples from each population.
(c) Find or estimate the P-value of the sample test statistic.
(Use 4 decimal places.)
p-value > 0.200
0.100 < p-value < 0.200
0.050 < p-value < 0.100
0.020 < p-value < 0.050
0.002 < p-value < 0.020
p-value < 0.002
(d) Based on your answers in parts (a) to (c), will you reject
or fail to reject the null hypothesis?
At the α = 0.05 level, we reject the null hypothesis and conclude
the data are not statistically significant.
At the α = 0.05 level, we reject the null hypothesis and conclude
the data are statistically significant.
At the α = 0.05 level, we fail to reject the null hypothesis and
conclude the data are not statistically significant.
At the α = 0.05 level, we fail to reject the null hypothesis and
conclude the data are statistically significant.
(e) Interpret your conclusion in the context of the
application.
Fail to reject the null hypothesis, there is sufficient evidence
that the variance in percentage yields on assets is greater in the
French companies.
Reject the null hypothesis, there is insufficient evidence that the
variance in percentage yields on assets is greater in the French
companies.
Reject the null hypothesis, there is sufficient evidence that the
variance in percentage yields on assets is different in both
companies.
Fail to reject the null hypothesis, there is insufficient evidence
that the variance in percentage yields on assets is different in
both companies.
(a) level = 0.05
Ho: σ12 = σ22; H1: σ12 ≠ σ22
(b) F = 2.00
dfN = 20
dfD = 17
The populations follow independent normal distributions. We have
random samples from each population.
(c) p-value = 0.0768
0.050 < p-value < 0.100
(d) At the α = 0.05 level, we fail to reject the null hypothesis
and conclude the data are not statistically significant.
(e) Fail to reject the null hypothesis, there is insufficient
evidence that the variance in percentage yields on assets is
different in both companies.
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