MCQs of Statistics – STATISTICAL INFERENCE AND ESTIMATION

A_______ is the specific value of the statistic used to estimate the population parameter.

An estimator Q is an unbiased estimator of the population parameter Q if _________

Since E(X) _______X is said to be unbiased estimator of the population mean.

Sample proportion P is ______ estimator

Sample variance S₂ is unbiased estimator of population variance ²6 because _______

Sampling Error decrease by ____ the sample size.

x=40 is estimator of ________

________ is a value of sample statistics

_____ is an estimate expressed by a single value.

_______ is the process of using sample information to reach

The Estimation and testing of hypothesis are main branches of _______

The minimum variance unbiased estimator of the population mean is _______

95% confidence limits u are _______

95% confidence limits for P are _______

E(x₁ – x₂)= _________

The hypothesis which is being tested is called ___________

Which of the following is simple hypothesis________

Type II error is committed when the null hypothesis is _________

If n = 400 and P=.69 then 90% C.I for P is _______

Which of the following cannot be H_o__________

The level of significance is denoted by _______

If H_o is stated as Q = Q_o< the alternate hypothesis in general stated______

The values that separate the region of rejection and acceptance region are called ______

The first and starting point in test Hypothesis is ______

Power of test is denoted by ________

Criteria to check a point estimator to be good are

1 – α  is the probability of

Parameter is a ______ quantity

Consistency of an estimator can be checked by comparing

If we reject the null hypothesis, we might be making

Herbicide A has been used for years in order to kill a particular type of weed. An experiment is to be conducted in order to see whether a new herbicide, Herbicide B, is more effective than Herbicide A. Herbicide A will continue to be used unless there is sufficient evidence that Herbicide B is more effective. The alternative hypothesis in this problem is

Analysis of Variance (ANOVA) is a test for equally of

A quantity obtained by applying certain rule or formula is known as __________

Which of the following is an assumption underlying the use of the t-distribution?

For t distribution, increasing the sample size, the affect will be on?

The t distribution are

condition for applying Central Limit Theorem (CLT) which approximate the sampling distribution of the mean with a normal distribution is?

Which of the following is a true statement for comparing the t distribution with standard normal.

what is the probability of a type II error when α=0.05?

The critical value of a test statistic is determined from

The Mann-Whitney U test is preferred to a t-test when

In testing for the difference between two populations, it is possible to use

The sign test assumes that the

The Runs test results in rejecting the null hypothesis of randomness when

Three brands of coffee are rated for tasted on a scale of 1 to 10. Six persons are asked to rate each brand so that there is a total of 18 observations.The appropriate test to tasted equally good is

Comparing the times to failure of radar transponders made by firms A, B, and C based on an airline’s sample experience with the three types of instruments one may use

To perform a Runs test for randomness the data must be

The Wilcoxon, Rank-Sum test used to compares

The Spearman Rank-Correlation test requires that the

Which of the following test must be two-sided?

In a Wilcoxon Rank-Sum test

Which of the following test is most likely assessing this null hypothesis: H_o The number of violations per apartment in the population of all city apartments is binomially distributed with a probability of success in any one trial of P=0.3 dd

When using the sign test, if two scores are tied, then

When testing for randomness, we can use

Wilcoxon Rank-Sum test can be of

The non parametric equivalent of an unpaired samples t-test

Which of the following test use Rank Sums

Let X1,X2,……,Xn be a random sample from a density,,,, _f(x ι θ)
where θ is a value of the random variable Θwith known density gΘ(θ) Then the estimator ∏(θ) with…/ respect to the prior gΘ(θ) is define as…………………………..E[∏(θ)ιX1,X2,…..,Xn] is called

if f(x1,x2,…xn;θ)=g(θˆ;θ)h(x1,x2,….,xn), then θˆ is

if Var(T2)

if Var(θˆ)→0 as n → 0, then θˆ is said to be

for two estimators T1=t1(X1,X2,….Xn) and T1=t1(X1,X2,….Xn) then estimators t1 is defined to be Rt1(θ)≤Rt2(θ) for all θ in Θ

Let X1,X2,…Xn be a random sample from the density f(x;(θ), where θ may be vector. If the conditional distribution of X1,X2,…Xn given S=s does not depend on θ for any value of s of S, then statistic is called.

If E(θˆ)=θ, then θˆ is said to be

Let Z1,Z2,….Zn be independent and identically distributedrandom variable, satisfying E[ι Zt ι]<∞. Let N be an integer valued random variable whose value n depends only on the values of the first n Z¡'s. Suppose E(N)< ∞, then E(Z1,Z2,....Zn)=E(N)E(Z) is called

If the conditional distribution of X1,X2,…..Xn given S=s, does not depends on θ, for any value of S=s the statistics S=s(X1,X2,…..Xn) is called

For a biased estimator θˆ of θ, which one is corect

A test is said to be most powerful test of size α, if

A set of jointly sufficient statistic is defined to be minimal sufficient if and only if