In the last quarter of 2007, a group of 64 mutual funds had a mean return of 3.9% with a standard deviation of 6.7%. If a normal model can be used to model them, what percent of the funds would you expect to be in each region? Use the 68-95-99.7 rule to approximate the probabilities rather than using technology to find the values more precisely. Be sure to draw a picture first

Step-by-step explanation:

In a normal curve, the empirical rule states that 68% of data falls within 1 standard deviation of the mean.  This means for this problem, 68/2 = 34% of data falls from

4.8-5.8 = -1 to 4.8, and 34% falls from 4.8 to

4.8+5.8 = 10.6.

95% of data falls within 2 standard deviations of the mean.  This includes the 68%; this means this leaves 95-68 = 27/2 = 13.5% to fall from

-1-5.8 = -6.8 to -1, and 13.5% falls from 10.6 to

10.6+5.8 = 16.4.

99.7% of data falls within 3 standard deviations of the mean.  This includes the 95%; this means this leaves 99.7-95 = 4.7/2 = 2.35% to fall from

-6.8-5.8 = -12.6 to -6.8, and 2.35% falls from 16.4 to

16.4+5.8 = 22.2.

This leaves 100-99.7 = 0.3/2 = 0.15% to fall from the left end to -12.6, and 0.15% to fall from 22.2 to the right end.

For part a,

For returns of 10.6 or more, we would add everything above this value:

13.5+2.35+0.15 = 16%.

For part b,

Since 4.8 is the mean, 50% of data falls below this.

For part c,

-12.6 is 3 standard deviations from the mean, and 22.2 is 3 standard deviations from the mean.  This means that 99.7% of the data falls between these values.

For part d,

We add together all values above 16.4:  2.35+0.15 = 2.5%

problem:

f(x) = - 2/3x + 5; f(5/2)

substitute 5/2 in for x:

f(5/2) = -2/3(5/2) + 5

simplify the right side:

f(5/2) = -5/3 + 5

f(5/2) = 10/3

f(5/2) = 10/3

i hope this !