ICS Part 2 Statistics Chapter 12 Online Test

The following statistic are unbiased estimators:

• The Sample mean A
• S² = Σ(X - X)²/n-1 B
• The sample proportion C
• All the above D

If 1-α = 0.90, the value of Z_a/2 is:

• 1.645 A
• 1.96 B
• 2.326 C
• 2.575 D

If the observations are paired and the number of pairs is n, then the number of degree of freedom is equal to

• n A
• n - 1 B
• 2n C
• 2n - 1 D

Level of significance is denoted by

• 2 - α A
• 3 - α B
• α C
• 1 - α D

(1-α) is called:

• Critical value A
• Level of significance B
• Level of confidence C
• Interval estimate D

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

• 
  A
• 
  B
• 
  C
• 
  D

• best estimators A
• biased estimators B
• unbiased estimators C
• normal estimators D

A specific value of an estimator computed from the sample data is called

• estimation A
• estimate B
• interval estimate C
• point estimate D

Estimation is of two types:

• One sides and two sides A
• Type I and type II B
• Point estimation and interval estimation C
• Biased and unbiased D

Types of statistical inferences are

• one A
• two B
• three C
• four D

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

• Confidence interval A
• Confidence coefficient B
• Confidence limits C
• Level of significance D

Statistical inference has two branches namely:

• Level of confidence and degrees of freedom A
• Biased estimator and unbiased estimator B
• Point estimate and interval estimate C
• Estimation of parameter and testing of hypothesis D

Large sample contains more than

• 5 values A
• 10 values B
• 20 values C
• 30 values D

The standard error of the estimate increased by decreasing

• population A
• sample size B
• errors C
• precision D

The distance between an estimate and the estimated parameter is called:

• Sampling error A
• Standard error B
• Bias C
• Error of estimation D

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

• Decreased A
• Increased B
• Constant C
• Same D

If mean of the sampling distribution is equal to the parameter then the estimator will be

• biased A
• consistent B
• sufficient C
• unbiased D