Estimation

The value corresponding to a significance level that determines those test statistics that lead to rejection of null hypothesis and those that lead to a decision not to reject null hypothesis is referred to as

Critical Value

correct

A confidence interval gives a range estimate of values

we never really know whether the confidence interval includes the true population mean or proportion, or not.

Because we only select one sample, and μ or π are unknown

An interval of numbers around the point estimate, that has a fixed "confidence level" of containing the parameter value, Called a confidence interval.

Interval estimate

A single statistic value that is the "best guess" for the parameter value

Point estimate

is a probability that represents the percentage of intervals that will contain if a large number of repeated samples are obtained.

The Level of Confidence in a confidence interval

the chance we take that the true population parameter is not contained in the confidence interval.

The level of significance, or "α" risk

a 95% confidence interval would have

an "α" of 5%

Confidence Interval of a parameter consists of

an interval of numbers along with a probability that the interval contains the unknown parameter

a function of the data or sample that is used to infer the value of an unknown parameter population in a statistical model.

estimator

An unbiased estimator is said to be consistent if

he difference between the estimator and the parameter grows smaller as the sample size grows larger.

draws inferences about a population by estimating the value of an unknown parameter using an interval.

interval estimator

draws inferences about a population by estimating the value of an unknown parameter using a single value or point.

point estimator

If there are two unbiased estimators of a parameter, the one whose variance is smaller is said to be

relatively efficient.

A confidence interval estimate of 100% would be

so wide as to be meaningless for practical decision making

true

the estimator, the quantity of interest (the estimand or parameter), and its result (the estimate) are different from each other.

is used to estimate the population mean µ.

the sample mean X

The objective of estimation is

to approximate the value of a population parameter on the basis of a sample statistic.

an estimator whose expected value is equal to that parameter.

unbiased estimator of a population parameter

Qualities desirable in estimators include

unbiasedness, consistency, and relative efficiency:

the proportion in the tails of the sampling distribution that is outside the established confidence interval.

α