Introduction to Mathematical StatisticsAn exceptionally clear and impeccably accurate presentation of statistical applications and more advanced theory. Included is a chapter on the distribution of functions of random variables as well as an excellent chapter on sufficient statistics. More modern technology is used in considering limiting distributions, making the presentations more clear and uniform. |
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Page 185
Let T have a {-distribution with 10 degrees of freedom. Find Pr (| T\ > 2.228) from
Table IV. 4.41. Let T have a /-distribution with 14 degrees of freedom. Determine
b so that Pr {-b < T < b) = 0.90. 4.42. Let Fhave an F-distribution with parameters r
...
Let T have a {-distribution with 10 degrees of freedom. Find Pr (| T\ > 2.228) from
Table IV. 4.41. Let T have a /-distribution with 14 degrees of freedom. Determine
b so that Pr {-b < T < b) = 0.90. 4.42. Let Fhave an F-distribution with parameters r
...
Page 192
Let XuX2,Xy denote a random sample from a standard normal distribution. Let
the random variables Yx, Y2, Y3 be defined ... (a) Show that y, has a beta
distribution with parameters a = a! and p = a2 + . . . + at + 1. (b) Show that y, + . . +
yr, r < k, ...
Let XuX2,Xy denote a random sample from a standard normal distribution. Let
the random variables Yx, Y2, Y3 be defined ... (a) Show that y, has a beta
distribution with parameters a = a! and p = a2 + . . . + at + 1. (b) Show that y, + . . +
yr, r < k, ...
Page 372
parameters a,, a2, and a3 (see Example 1, Section 4.5). Show that the
conditional distribution of 0, and 02 is Dirichlet and determine the conditional
means E(&i\yuy2) and E(&2\yuy2). 8.6. Let X be N(0, 1/0). Assume that the
unknown 9 is a ...
parameters a,, a2, and a3 (see Example 1, Section 4.5). Show that the
conditional distribution of 0, and 02 is Dirichlet and determine the conditional
means E(&i\yuy2) and E(&2\yuy2). 8.6. Let X be N(0, 1/0). Assume that the
unknown 9 is a ...
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Accordingly approximate best critical region chi-square distribution complete sufficient statistic conditional p.d.f. conditional probability confidence interval Consider continuous type converges in probability correlation coefficient critical region defined degrees of freedom denote a random depend upon 9 discrete type distribution function F(x distribution with mean distribution with p.d.f. distribution with parameters equation estimator of 9 Example Exercise F-distribution gamma distribution given H0 is true hypothesis H0 independent random variables integral joint p.d.f. Let the random Let Xu X2 limiting distribution marginal p.d.f. matrix moment-generating function order statistics p.d.f. of Xu percent confidence interval Poisson distribution positive integer probability density functions probability set function quadratic form random experiment random sample random variables Xx reject H0 respectively sample space Section Show significance level simple hypothesis statistic for 9 sufficient statistic testing H0 theorem unbiased estimator variance a2 Xx and X2 Yu Y2 zero elsewhere