 6.4.1BSC: Minting Quarters In a recent year, the U.S. Mint in Denver manufact...
 6.4.7BSC: In Exercises, use the same population of {4, 5, 9} that was used in...
 6.4.8BSC: Exercises, use the same population of {4, 5, 9} that was used in Ex...
 6.4.9BSC: In Exercises, use the same population of {4, 5, 9} that was used in...
 6.4.2BSC: Sampling with Replacement In a recent year, the U.S. Mint in Denver...
 6.4.3BSC: Unbiased Estimators Data Set 1 includes a sample of 40 pulse rates ...
 6.4.16BSC: Births: Sampling Distribution of Sample Proportion When three birth...
 6.4.17BSC: SAT and ACT Tests Because they enable efficient procedures for eval...
 6.4.18BSC: Quality Control After constructing a new manufacturing machine, fiv...
 6.4.10BSC: In Exercises, use the same population of {4, 5, 9} that was used in...
 6.4.11BSC: In Exercises, use the population of ages {56, 49, 58, 46} of the fo...
 6.4.12BSC: In Exercises, use the population of ages {56, 49, 58, 46} of the fo...
 6.4.13BSC: In Exercises, use the population of ages {56, 49, 58, 46} of the fo...
 6.4.14BSC: In Exercises, use the population of ages {56, 49, 58, 46} of the fo...
 6.4.15BSC: Births: Sampling Distribution of Sample Proportion When two births ...
 6.4.4BSC: Sampling Distribution Data Set 20 includes a sample of weights of 1...
 6.4.5BSC: Good Sample? For the population of all college students currently t...
 6.4.6BSC: Lottery Results Many states have a Pick 3 lottery in which three di...
 6.4.19BB: Using a Formula to Describe a Sampling Distribution Exercise requir...
 6.4.20BSC: Mean Absolute Deviation Is the mean absolute deviation of a sample ...
Solutions for Chapter 6.4: Elementary Statistics 12th Edition
Full solutions for Elementary Statistics  12th Edition
ISBN: 9780321836960
Solutions for Chapter 6.4
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Elementary Statistics, edition: 12. Chapter 6.4 includes 20 full stepbystep solutions. Since 20 problems in chapter 6.4 have been answered, more than 188875 students have viewed full stepbystep solutions from this chapter. Elementary Statistics was written by and is associated to the ISBN: 9780321836960.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

2 k p  factorial experiment
A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Bivariate distribution
The joint probability distribution of two random variables.

C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defectsperunit or U chart.

Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

Conditional variance.
The variance of the conditional probability distribution of a random variable.

Confounding
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

Correction factor
A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

Correlation
In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

Expected value
The expected value of a random variable X is its longterm average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

Experiment
A series of tests in which changes are made to the system under study

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .