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Statistics for Decision- Making in Business - Maricopa Community ...

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Repair Cost<br />

Mean 971<br />

Standard Error 382<br />

Median 738<br />

Mode -<br />

Standard Deviation 1,207<br />

Sample Variance 1,455,875<br />

Kurtosis 7<br />

Skewness 2<br />

Range 4,194<br />

M<strong>in</strong>imum -<br />

Maximum 4,194<br />

Sum 9,707<br />

Count 10<br />

Due to the great variability <strong>in</strong> repair costs, it would be most appropriate to use the<br />

median as measure of center. It also reflects the fact that most repair costs, if there<br />

are any, tend to be between $600 and $1000. S<strong>in</strong>ce the standard deviation<br />

describes movement about the mean, it is not appropriate to be used <strong>in</strong><br />

comb<strong>in</strong>ation with a median. Thus, we should probably use the <strong>in</strong>terquartile range<br />

to describe the middle 50% of repair costs.<br />

b.<br />

The repair costs of $4,194 is nearly 3 standard deviations above the mean. This<br />

means that it is an outlier cost.<br />

c. Accord<strong>in</strong>g to C.T., at least . / of the data <strong>in</strong> this data set should be<br />

with<strong>in</strong> 2.7 standard deviations of the mean. Thus, there is only a 14% chance that<br />

we have a score outside of 2.7 standard deviations of the mean. This tells us that a<br />

repair cost of $4,194 is fairly unusual.<br />

6.<br />

<strong>Statistics</strong> <strong>for</strong> <strong>Decision</strong>-<strong>Mak<strong>in</strong>g</strong> <strong>in</strong> Bus<strong>in</strong>ess © Milos Podmanik Page 227

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