CH 7

stratified random sampling

In ______, the population is divided up into mutually exclusive and collectively exhaustive groups called strata. The sample consists of randomly-selected elements from each stratum.

Statistical Quality Control

When a firm applies statistical techniques to develop and maintain its ability to produce high-quality goods and services, it is implementing statistical (BLANK) (BLANK)

Detection

A preferred approach to quality control is the (BLANK) approach.

random variable

x bar

A firm uses acceptance sampling when (BLANK)

it produces a product and at the end of the process, inspects a portion.

z

(x bar - u)/[(SD)/nsq.rt.

constant

A parameter is a (BLANK), although its value may be unknown.

Which of the following is true about a sample statistic such as the sample mean or sample proportion?

A sample statistic is a random variable.

sampling distribution

Blank 2 bar , Incorrect Unavailable is simply the probability distribution derived from all possible samples of a given size from the population.

Unbiased

P bar is an estimator of p

SD P bar equation

Sq.rt (p(1-p)/n)

Estimator

When a sample statistic is used to make inferences about a population parameter, it is referred to as an (BLANK).

NONRESPONSE BIAS

those responding to a survey or poll differ systematically from the non-respondents.

all items of interest

in a statistical problem, a population consists of (BLANK)

The purpose of statistical quality control is to (BLANK)

maintain high-quality goods and services.

cluster sampling

(BLANK) involves dividing a population into mutually exclusive and exhaustive groups, called clusters, and then selecting a random sample from these clusters for analysis.

Census

A (BLANK) is representative of population data

Which of the following statements is MOST accurate?

A parameter is a constant although its value may be unknown.

estimate

A particular value of an estimator is called an (BLANK)

Normally

A control chart is valid only if the sampling distribution of the relevant estimator is (approximately) (BLANK) distributed.

1. less 2. than

In general, the variability between sample means (BLANK) (BLANK) is the variability between observations.

Precision

The estimators must be multiplied by a correction factor. This correction factor, called the finite population correction factor, accounts for the added (BLANK) gained by sampling a larger percentage of the population.

Successes

The expected value of P is the proportion of (BLANK) in the population.

Bias

When the information from a sample is not typical of information in the population in a systematic way, we say that (BLANK) has occurred.

Bias

If a sample statistic consistently over- or under-estimates a population parameter, then there is (BLANK)

estimate sign

sample distribution sign = x bar

Selection bias occurs when

there is a systematic exclusion of certain groups from consideration for the sample.

Population

a (BLANK) consists of all items of interest in a statistical problem.

census

a (BLANK) is representative of population data

Sample

a subset of the population

Population

all items of interest in the statistical problem

The central limit theorem states that, for any distribution, as n gets larger, the sampling distribution of the sample mean becomes (BLANK)

closer to a normal distribution.

X bar

random

average

The CLT states that (BLANK) of a large number of independent observations from the same underlying distribution has an approximate normal distribution.

5

The general rule for using the finite correction factor is that the sample constitutes at least (BLANK) percent of the population.

inferential/inference

The branch of statistics that uses sample statistics to estimate a population parameter or test a hypothesis about such a parameter is BEST referred to as (BLANK) statistics

SD/ sq root (n)

The standard deviation of the sampling distribution of X is calculated as

Centerline

All sample estimates are plotted with reference to a (BLANK)

p bar chart

This type of chart monitors the proportion of defectives (or some other characteristic) in a production process.

n>= 0.05N

We can use the finite population correction factor when (BLANK)

1. static 2. parameter

We use a calculated sample (BLANK) to make inference about an unknown population (BLANK)

The sample is not representative of the population we are trying to describe.

Which of these is a characteristic of a "bad" sample? The statistic computed from the sample has no selection bias. The sample is typical of information in the population in a systematic way. The statistic computed from sample has no nonresponse bias. - The sample is not representative of the population we are trying to describe.

A sample statistic is considered biased if

it systematically over- or under-estimates the unknown parameter being estimated.

A firm using the detection approach inspects the production process and determines at which point the production process does not conform to .

specs/ specifications

If we had access to data that included the entire population, then the values of the parameters would be known and no statistical inference would be required.

true

Always normally distributed

If the population from which the sample is drawn is normally distributed, then the sampling distribution of the sample mean is

larger

If the sample size is (BLANK) relative to the population size, then the standard errors of the estimators must be multiplied by a correction factor.

3

In general, the control limits of a control chart are set at (BLANK) standard deviations from the centerline.

Chance

(BLANK) variation is not generally considered to be under the control of the individual worker or machine.

Which of the following is are components of a control chart?

Centerline Lower control limit (LCL) Upper control limit (UCL)