Answer:
We can first order the data from smallest value to largest value:
461
549
745
1500
1800
2000
3750
4795
68000
a) The mean is 9289, and the median is 1800
b) The data does have an outlier, which is 68000, because it is more that three standards deviations away from the mean, excluding this value, our new mean is 1950 and our new median is 1650. We can see that the greatest change in value was for the mean.
c) the median is more appropriate because the median is less sensitive to outliers. The mean can be easily swayed by outliers in either way, and this can give an erroneous impression of the data.
The expected annual medical expenses of a high-risk person is $3000 per year while that of a low-risk person is $1000 per year.
The expected annual medical expenses of a high-risk person will be calculated as:
= Probability of falling ill × Expenses in case of illness
= 30% × $10000
= 0.3 × $10000
= $3000
The expected annual medical expenses of a low-risk person will be calculated as:
= Probability of falling ill × Expenses in case of illness
= 10% × $10000
= 0.1 × $10000
= $1000
It should be noted that in a situation where the individuals are risk neutral, the low-risk persons will not buy insurance as only the high-risk individuals will be expected to buy<em> insurance.</em>
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Let's see there's forming, storming, norming and performing. I would use teambuilding during forming to limit the amount of storming in the next stage.
