## Introduction to Mathematical Statistics |

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Page 2

The ratio f/N is

. A relative frequency is usually quite erratic for small values of N, as you can

discover by tossing a coin. But as N increases, experience indicates that relative

...

The ratio f/N is

**called**the relative frequency of the event A in these N experiments. A relative frequency is usually quite erratic for small values of N, as you can

discover by tossing a coin. But as N increases, experience indicates that relative

...

Page 16

In this section, we shall see that some distributions can be described more simply

by what is to be

distributions that we shall describe by a probability density function are

In this section, we shall see that some distributions can be described more simply

by what is to be

**called**the probability density function. The two types ofdistributions that we shall describe by a probability density function are

**called**, ...Page 255

Such a rule is

hypothesis H1: 6 - 75. There is no bound on the number of rules or tests which

can be constructed. We shall consider three such tests. Our tests will be

constructed ...

Such a rule is

**called**a test of the hypothesis Ho: 0 < 75 against the alternativehypothesis H1: 6 - 75. There is no bound on the number of rules or tests which

can be constructed. We shall consider three such tests. Our tests will be

constructed ...

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accept accordance Accordingly alternative approximately assume called cent Chapter complete compute conditional confidence interval Consider constant continuous type critical region decision defined definition degrees of freedom denote a random depend determine discrete type distribution function equal Equation event Example EXERCISES exists expected fact given Hence inequality integral interval joint p.d.f. Let X1 likelihood marginal matrix maximum mean moment-generating function mutually stochastically independent normal distribution Note observed order statistics outcome parameter Pr(X probability density functions problem proof prove random experiment random interval random sample random variable ratio reject respectively result sample space Show significance level simple hypothesis ſº stochastically independent sufficient statistic symmetric matrix Table theorem transformation true unknown variance write X1 and X2 zero elsewhere