 3.4.1: identify the fivenumber summary and find the interquartile range.8...
 3.4.2: Identify the fivenumber summary and find the interquartile range.1...
 3.4.3: identify the fivenumber summary and find the interquartile range.3...
 3.4.4: identify the fivenumber summary and find the interquartile range.1...
 3.4.5: identify the fivenumber summary and find the interquartile range.1...
 3.4.6: identify the fivenumber summary and find the interquartile range.9...
 3.4.7: use each boxplot to identify the maximum value, minimum value, medi...
 3.4.8: use each boxplot to identify the maximum value, minimum value, medi...
 3.4.9: use each boxplot to identify the maximum value, minimum value, medi...
 3.4.10: use each boxplot to identify the maximum value, minimum value, medi...
 3.4.11: Earned Run Average—Number of Games Pitched Construct a boxplot for ...
 3.4.12: Innings Pitched Construct a boxplot for the following data which re...
 3.4.13: Teacher Strikes The number of teacher strikes over a 13–year period...
 3.4.14: Visitors Who Travel to Foreign Countries Construct a boxplot for th...
 3.4.16: Size of Dams These data represent the volumes in cubic yards of the...
 3.4.18: Number of Tornadoes A four–month record for the number of tornadoes...
 3.4.1E: Problem? 1 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.2E: Problem? 2 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.3E: Problem? 3 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.4E: Problem? 4 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.5E: Problem? 5 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.6E: Problem? 6 ? E identify? ?the? ?fivenumber? ?summary? ?and? ?find?...
 3.4.7E: Problem? 7 ? E use? ?each? ?boxplot? ?to? ?identify? ?the? ?maximum...
 3.4.8E: Problem? 8 ? E use? ?each? ?boxplot? ?to? ?identify? ?the? ?maximum...
 3.4.9E: Problem? 9 ? E use? ?each? ?boxplot? ?to? ?identify? ?the? ?maximum...
 3.4.10E: Problem? ?10E use? ?each? ?boxplot? ?to? ?identify? ?the? ?maximum?...
 3.4.11E: Problem? ?11E Earned? ?Run? ?Average—Number? ?of? ?Games? ?Pitched?...
 3.4.12E: Problem? ?12E Innings? ?Pitched?? ?Construct? ?a? ?boxplot? ?for? ?...
 3.4.13E: Problem? ?13E Teacher? ?Strikes?? ?The? ?number? ?of? ?teacher? ?st...
 3.4.14E: Problem? ?14E Visitors? ?Who? ?Travel? ?to? ?Foreign? ?Countries?? ...
 3.4.16E: Problem? ?16E Size? ?of? ?Dams?? ?These? ?data? ?represent? ?the? ?...
 3.4.18E: Problem? ?18E Number? ?of? ?Tornadoes?? ?A? ?four–month? ?record? ?...
Solutions for Chapter 3.4: Elementary Statistics: A Step By Step Approach 9th Edition
Full solutions for Elementary Statistics: A Step By Step Approach  9th Edition
ISBN: 9780073534985
Solutions for Chapter 3.4
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 32 problems in chapter 3.4 have been answered, more than 126685 students have viewed full stepbystep solutions from this chapter. Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985. Chapter 3.4 includes 32 full stepbystep solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9.

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

aerror (or arisk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

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

Average run length, or ARL
The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Bivariate normal distribution
The joint distribution of two normal random variables

Box plot (or box and whisker plot)
A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

Conidence level
Another term for the conidence coeficient.

Correlation matrix
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the offdiagonal elements rij are the correlations between Xi and Xj .

Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.

Error of estimation
The difference between an estimated value and the true value.

Event
A subset of a sample space.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

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.

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

Gaussian distribution
Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.

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 .