A certain mutual fund invests in both U.S. and foreign markets. Let x be a random variable that represents the monthly percentage return for the fund. Assume x has mean μ = 1.9% and standard deviation σ = 0.5%.
(a) The fund has over 500 stocks that combine together to give the overall monthly percentage return x. We can consider the monthly return of the stocks in the fund to be a sample from the population of monthly returns of all world stocks. Then we see that the overall monthly return x for the fund is itself an average return computed using all 500 stocks in the fund. Why would this indicate that x has an approximately normal distribution? Explain. Hint: See the discussion after Theorem 6.2.
The random variable ---Select--- x-bar x is a mean of a sample size n = 500. By the ---Select--- law of large numbers theory of normality central limit theorem , the ---Select--- x-bar x distribution is approximately normal.
(b) After 6 months, what is the probability that the
average monthly percentage return x will be
between 1% and 2%? Hint: See Theorem 6.1, and assume that
xhas a normal distribution as based on part (a). (Round
your answer to four decimal places.)
(c) After 2 years, what is the probability that x will be
between 1% and 2%? (Round your answer to four decimal
places.)
(d) Compare your answers to parts (b) and (c). Did the probability
increase as n (number of months) increased?
YesNo
Why would this happen?
The standard deviation ---Select--- increases decreases stays the same as the ---Select--- average mean sample size distribution increases.
(e) If after 2 years the average monthly percentage return was less
than 1%, would that tend to shake your confidence in the statement
that μ = 1.9%? Might you suspect that μ has
slipped below 1.9%? Explain.
This is very unlikely if μ = 1.9%. One would suspect that μ has slipped below 1.9%.This is very likely if μ = 1.9%. One would not suspect that μ has slipped below 1.9%. This is very unlikely if μ = 1.9%. One would not suspect that μ has slipped below 1.9%.This is very likely if μ = 1.9%. One would suspect that μ has slipped below 1.9%.
The random variable x-bar is a mean of a sample size n = 500. By the central limit theorem , the x-bar distribution is approximately normal.
b)
sample size =n= | 6 |
std error=σx̅=σ/√n= | 0.204 |
probability =P(1<X<2)=P((1-1.9)/0.204)<Z<(2-1.9)/0.204)=P(-4.41<Z<0.49)=0.6879-0=0.6879 |
c)
probability =P(1<X<2)=P((1-1.9)/0.102)<Z<(2-1.9)/0.102)=P(-8.82<Z<0.98)=0.8365-0=0.8365 |
d)
Yes
The standard deviation decreases as the sample size increases.
e)
This is very unlikely if μ = 1.9%. One would suspect that μ has slipped below 1.9%.
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