Question # 1

Estimation is of two types:

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One sides and two sides

Type I and type II

Point estimation and interval estimation

Biased and unbiased

If (1-α) is increased, the with of a confidence interval is:

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Decreased

Increased

Constant

Same

Types of statistical inferences are

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one

two

three

four

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best estimators

biased estimators

unbiased estimators

normal estimators

The standard error of the estimate increased by decreasing

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population

sample size

errors

precision

100(1-α)% confidence interval for population proportion of success,&=nbsp;π is

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P (L <μ < U) = 1 - α

P (L <σ < U) = 1 - α

P (L <π< U) = 1 - α

P (L <P&=nbsp;< U) = 1 - α

Estimate is the observed value of an:

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Unbiased estimator

Estimation

Estimator

Interval estimation

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biased

unbiased

positively biased

none of these

The following statistic are unbiased estimators:

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The Sample mean

S² = Σ(X - X)²/n-1

The sample proportion

All the above

The process of making estimates about the population parameter from a sample is called:

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Statistical independence

Statistical inference

Statistical hypothesis

Statistical decision

The probability associated with confidence interval is called:

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Level of confidence

Confidence coefficient

Both A and B

Confidence limits

If population proportion (P) is unknown, the standard error of the sample proportion (p) can be estimated by the formula

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(1-α) is called:

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Critical value

Level of significance

Level of confidence

Interval estimate

The precision can be increased by ---------------- the sample size

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increasing

decreasing

changing

ignoring

The difference of upper and lower limits of confidence interval measures the

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level of significance

level of confidence

interval

precision

A range of values within which the population parameter is expected:

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Confidence interval

Confidence coefficient

Confidence limits

Level of significance

If 1-α = 0.90, the value of Z_a/2 is:

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1.645

1.96

2.326

2.575

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