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Suppose that a point(X, Y, Z)is to be chosen at random in three-dimensional space, whereX,Y, andZare independent random variables, and each has the standard normal distribution. What is the probability that the distance from the origin to the point will be less than 1 unit?

Short Answer

Expert verified

\(P\left( {{X^2} + {Y^2} + {Z^2} \le 1} \right) < 0.2\)

Step by step solution

01

Given information

X, Y, and Z are independent random variables, and each of the variables follows the standard normal distribution.

02

Calculate the probability

Since \({X^2} + {Y^2} + {Z^2}\)has \({\chi ^2}\)distributed with degrees of freedom 3.

Referring to the table at the end of the book for the answer.

Hence, \(P\left( {{X^2} + {Y^2} + {Z^2} \le 1} \right) < 0.2\).

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Most popular questions from this chapter

In the June 1986 issue of Consumer Reports, some data on the calorie content of beef hot dogs is given. Here are the numbers of calories in 20 different hot dog brands:

186,181,176,149,184,190,158,139,175,148,

152,111,141,153,190,157,131,149,135,132.

Assume that these numbers are the observed values from a random sample of twenty independent standard random variables with meanμand variance \({{\bf{\sigma }}^{\bf{2}}}\), both unknown. Find a 90% confidence interval for the mean number of caloriesμ.

Continue the analysis in Example 8.6.2 on page 498. Compute an interval (a, b) such that the posterior probability is 0.9 that a <μ<b. Compare this interval with the 90% confidence interval from Example 8.5.4 on page 487.

Question:Suppose that a random variable X has the geometric distribution with an unknown parameter p (0<p<1). Show that the only unbiased estimator of p is the estimator \({\bf{\delta }}\left( {\bf{X}} \right)\) such that \({\bf{\delta }}\left( {\bf{0}} \right){\bf{ = 1}}\) and \({\bf{\delta }}\left( {\bf{X}} \right){\bf{ = 0}}\) forX>0.

In the situation of Example 8.5.11, suppose that we observe\({{\bf{X}}_{\bf{1}}}{\bf{ = 4}}{\bf{.7}}\;{\bf{and}}\;{{\bf{X}}_{\bf{2}}}{\bf{ = 5}}{\bf{.3}}\).

  1. Find the 50% confidence interval described in Example 8.5.11.
  2. Find the interval of possibleθvalues consistent with the observed data.
  3. Is the 50% confidence interval larger or smaller than the set of possibleθvalues?
  4. Calculate the value of the random variable\({\bf{Z = }}{{\bf{Y}}_{\bf{2}}}{\bf{ - }}{{\bf{Y}}_{\bf{1}}}\)as described in Example 8.5.11.
  5. Use Eq. (8.5.15) to compute the conditional probability that\(\left| {{{{\bf{\bar X}}}_{\bf{2}}}{\bf{ - \theta }}} \right|{\bf{ < 0}}{\bf{.1}}\)givenZ isequal to the value calculated in part (d).

Suppose that X1,……,Xn form a random sample from a normal distribution for which the mean is known and the variance is unknown. Construct an efficient estimator that is not identically equal to a constant, and determine the expectation and the variance of this estimator.

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