Question # 1

An automobile is driven on the average on more than 1600 kilometers per year, the null hypothesis is

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H_o : μ = 16000 kilometers

H_o : μ ≤ 16000 kilometers

H_o : μ < 16000 kilometers

H_o : μ > 16000 kilometers

An example in a two-sided, alternative hypothesis is:

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H₁ :u < 0

H₁ : u > 0

H₁ L u > 0

H₁ : u ≠ 0

P(type II error) is equal to:

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α

β

1 - α

1 - β

A ---------------- error is made by accepting H_o if H₁ is actually true

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type - I

type - II

type - III

type - IV

If Ho:π >πo , H1:π <πo and level of significance is=α then Ho will be rejected if

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Z < Z=α

Z=α/2 < Z

Z > Z1-α

Z < Z1-α

A hypothesis that specifies all the value of parameter is called:

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Statistical hypothesis

Simple hypothesis

Composite hypothesis

None of these

The values of test statistic which separate the rejection and non rejection regions for the test are called

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simple values

critical values

parametric values

none of these

The hypothesis which is tested for possible rejection is called

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common hypothesis

null hypothesis

alternative hypothesis

wrong hypothesis

The alternative hypothesis is also called:

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Null hypothesis

Statistical hypothesis

Research hypothesis

Simple hypothesis

1 -&=nbsp;α is call:

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Confidence coefficient

Power of the test

Size of the test

Level of significance

A quantitative statement about a population is called:

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Research hypothesis

Composite hypothesis

Simple hypothesis

Statistical hypothesis

The choice of one-tailed test and two tailed test depends upon:

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Composite hypothesis

Null hypothesis

Alternative hypothesis

Simple hypothesis

A statistical hypothesis is an assertion or conjecture about the distribution of random variables

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one

two

one or more

three

If the null hypothesis is false, we many accept it leading to a ----------- decision

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true

correct

wrong

none of these

If critical region is located equally in both tails of the sampling distribution of test statistic, the test is called ------------- test

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one tailed

two tailed

left tailed

right tailed

The degree of confidence is equal to:

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β

1 - β

1 - α

α

A statistic on the basis of which a decision is made about the hypothesis of interest is called

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critical region

test statistic

parameter

rejection region

If we reject Ho when Ho is actually true then it is

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type - I error

type - II error

type - III error

type - IV error

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