2. A random sample of receipts for individuals eating at the Terrace Restaurant showed the sample mean to be X $10.39 with sample standard deviations = $2.15. (a) Use Chebyshev's Theorem to find the smallest interval centered on the mean in which we can expect at least 88.9% of the data to fall. (b) If our sample is normally distributed, what interval will contain exactly 95% of our data?
2. A random sample of receipts for individuals eating at the Terrace Restaurant showed the sample mean to be X $10.39 with sample standard deviations = $2.15. (a) Use Chebyshev's Theorem to find the smallest interval centered on the mean in which we can expect at least 88.9% of the data to fall. (b) If our sample is normally distributed, what interval will contain exactly 95% of our data?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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2. A random sample of receipts for individuals eating at the Terrace Restaurant showed the
sample mean to be X = $10.39 with sample standard deviation s = $2.15.
(a) Use Chebyshev's Theorem to find the smallest interval centered on the mean in
which we can expect at least 88.9% of the data to fall.
(b) If our sample is normally distributed, what interval will contain exactly 95% of our
data?
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A-
A-
AaßbCcDdEe
AabbCcDdEe
AaBbCcDd AaBbCcDdl AaBbCcDdEe
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Nermal
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Heading 2
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Heading 4
Heading 5
2. A random sample of receipts for individuals eating at the Terrace Restaurant showed the
sample mean to be X = $10.39 with sample standard deviation s = $2.15.
(a) Use Chebyshev's Theorem to find the smallest interval centered on the mean in
which we can expect at least 88.9% of the data to fall.
(b) If our sample is normally distributed, what interval will contain exactly 95% of our
data?
615 words
English (United States)
O Focus
Mac
吕0,
F2
F3
F7
FE
F9
@
$
%
&
*
2
3
4
5
6
8
9
W
E
R
U
P
D
F
G
H
K
C
V
В
N
M
Expert Solution
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Step 1
The normal distribution is used in statistics.
Using chebyshev's theorem, atleast 1-1/K2 values lies within k standard deviations.
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