Introduction to Mathematical Statistics |
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Page 170
... power of the test when Ho is true , the significance level of this test is ... function of the test . 9.2 . Let X have a binomial distribution with ... power function of the test . = = 2 and 9.3 . Let X1 , X2 be a random sample of size n ...
... power of the test when Ho is true , the significance level of this test is ... function of the test . 9.2 . Let X have a binomial distribution with ... power function of the test . = = 2 and 9.3 . Let X1 , X2 be a random sample of size n ...
Page 178
... power function K ( 0 ) , 0 < 0 ≤ 14 , of this test . 1 = 1/0 , 0 < x < 0 , zero elsewhere . of a random sample of size 4 Y1 be y4 . We reject H。:0 = 1 Find the power function K ( 0 ) , 9.13 . Let X have a p.d.f. of the form f ( x ; 0 ) ...
... power function K ( 0 ) , 0 < 0 ≤ 14 , of this test . 1 = 1/0 , 0 < x < 0 , zero elsewhere . of a random sample of size 4 Y1 be y4 . We reject H。:0 = 1 Find the power function K ( 0 ) , 9.13 . Let X have a p.d.f. of the form f ( x ; 0 ) ...
Page 244
... power , 168 , 169 probability density , 13 , 14 probability set , 9 regression , 212 set , 4 Hypothesis , see Statistical hypothesis Jacobian , 67 , 78 Joint probability density function , 41 , 45 Koopman - Pitman form , 79 , 111 , 115 ...
... power , 168 , 169 probability density , 13 , 14 probability set , 9 regression , 212 set , 4 Hypothesis , see Statistical hypothesis Jacobian , 67 , 78 Joint probability density function , 41 , 45 Koopman - Pitman form , 79 , 111 , 115 ...
Contents
CHAPTER | 1 |
TRANSFORMATION OF VARIABLES cont | 17 |
CHAPTER | 27 |
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Common terms and phrases
A₁ A₂ best critical region binomial distribution c₁ cent confidence interval chi-square distribution composite hypothesis conditional p.d.f. confidence interval Consider continuous type critical region degrees of freedom denote a random discrete type distribution function distribution having p.d.f. distribution with mean EXAMPLE Exercises function of Y₁ hypothesis H₁ independent random variables integral Jacobian joint p.d.f. joint sufficient statistics Let the random Let X1 Let Y₁ limiting distribution marginal p.d.f. moment-generating function mutually stochastically independent Mx(t My(t normal distribution n(x null hypothesis null simple hypothesis one-to-one transformation order statistics p.d.f. of Y₁ p₁ Poisson distribution positive integer Pr(a Pr(X Pr(Y probability density functions r₁ random experiment random sample random variables X1 Show significance level statistical hypothesis stochastically independent random theorem type of random unbiased statistic values variance o² X₁ X1 and X2 X₂ Xn denote Y₂ zero elsewhere μ₁ σ²