 1.1.1: Give one possible sample of size 4 from each of the following popul...
 1.1.2: For each of the following hypothetical populations, give a plausibl...
 1.1.3: Consider the population consisting of all computers of a certain br...
 1.1.4: a. Give three different examples of concrete populations and three ...
 1.1.5: regularly with a small group of students enrolled in the course to ...
 1.1.6: The California State University (CSU) system consists of 23 campuse...
 1.1.7: A certain city divides naturally into ten district neighborhoods. H...
 1.1.8: The amount of flow through a solenoid valve in an automobiles pollu...
 1.1.9: In a famous experiment carried out in 1882, Michelson and Newcomb o...
 1.1.10: Consider the strength data for beams given in Example 1.2. a. Const...
 1.1.11: Every score in the following batch of exam scores is in the 60s, 70...
 1.1.12: The accompanying specific gravity values for various wood types use...
 1.1.13: Allowable mechanical properties for structural design of metallic a...
 1.1.14: The accompanying data set consists of observations on showerflow r...
 1.1.15: Construct a comparative stemandleaf display by listing stems in t...
 1.1.16: The article cited in Example 1.2 also gave the accompanying strengt...
 1.1.17: Temperature transducers of a certain type are shipped in batches of...
 1.1.18: d. Suppose that instead of the values 15, 16, and 17 being listed s...
 1.1.19: The number of contaminating particles on a silicon wafer prior to a...
 1.1.20: a. Construct a stemandleaf display using the thousands digit as t...
 1.1.21: The article cited in Exercise 20 also gave the following values of ...
 1.1.22: How does the speed of a runner vary over the course ofa marathon (a...
 1.1.23: In a study of warp breakage during the weaving of fabric (Technomet...
 1.1.24: The accompanying data set consists of observations on shear strengt...
 1.1.25: A transformation of data values by means of some mathematical funct...
 1.1.26: Automated electron backscattered diffraction is now being used in t...
 1.1.27: The paper Study on the Life Distribution of Microdrills (J. of Engr...
 1.1.28: Human measurements provide a rich area of application for statistic...
 1.1.29: Consider the following data on type of health complaint (J joint sw...
 1.1.30: A Pareto diagram is a variation of a histogram for categorical data...
 1.1.31: The cumulative frequency and cumulative relative frequency for a pa...
 1.1.32: Fire load (MJ/m2 ) is the heat energy that could be released per sq...
 1.1.33: The article The Pedaling Technique of Elite Endurance Cyclists (Int...
 1.1.34: Exposure to microbial products, especially endotoxin, may have an i...
 1.1.35: The minimum injection pressure (psi) for injection moldingspecimens...
 1.1.36: A sample of 26 offshore oil workers took part in a simulated escape...
 1.1.37: 1.4 Measures of Variability 31 continental temperature. Data presen...
 1.1.38: Blood pressure values are often reported to the nearest 5 mmHg (100...
 1.1.39: The propagation of fatigue cracks in various aircraft parts has bee...
 1.1.40: Compute the sample median, 25% trimmed mean, 10% trimmed mean, and ...
 1.1.41: A sample of n 10 automobiles was selected, and each was subjected t...
 1.1.42: a. If a constant c is added to each xi in a sample, yielding yi xi ...
 1.1.43: An experiment to study the lifetime (in hours) for a certain type o...
 1.1.44: The article Oxygen Consumption During Fire Suppression: Error of He...
 1.1.45: The value of Youngs modulus (GPa) was determined for cast plates co...
 1.1.46: The accompanying observations on stabilized viscosity (cP) for spec...
 1.1.47: Calculate and interpret the values of the sample median, sample mea...
 1.1.48: Exercise 34 presented the following data on endotoxin concentration...
 1.1.49: A study of the relationship between age and various visual function...
 1.1.50: In 1997 a woman sued a computer keyboard manufacturer, charging tha...
 1.1.51: The article A ThinFilm Oxygen Uptake Test for the Evaluation of Au...
 1.1.52: The first four deviations from the mean in a sample of n 5 reaction...
 1.1.53: Reconsider the data on area of scleral lamina given in Exercise 49....
 1.1.54: Consider the following observations on shear strength (MPa) of a jo...
 1.1.55: Here is a stemandleaf display of the escape time data introduced ...
 1.1.56: The amount of aluminum contamination (ppm) in plastic of a certain ...
 1.1.57: A sample of 20 glass bottles of a particular type was selected, and...
 1.1.58: A company utilizes two different machines to manufacture parts of a...
 1.1.59: Blood cocaine concentration (mg/L) was determined bothfor a sample ...
 1.1.60: Observations on burst strength (lb/in2 ) were obtained both for tes...
 1.1.61: The accompanying comparative boxplot of gasoline vaporcoefficients ...
 1.1.62: Consider the following information on ultimate tensilestrength (lb/...
 1.1.63: The amount of radiation received at a greenhouse plays an important...
 1.1.64: The following data on HC and CO emissions for one particular vehicl...
 1.1.65: The accompanying frequency distribution of fracture strength (MPa) ...
 1.1.66: A deficiency of the trace element selenium in the diet cannegativel...
 1.1.67: Aortic stenosis refers to a narrowing of the aortic valve in the he...
 1.1.68: a. For what value of c is the quantity (xi c)2 minimized? [Hint: Ta...
 1.1.69: a. Let a and b be constants and let yi axi b for i 1, 2, . . . , n....
 1.1.70: Elevated energy consumption during exercise continues after the wor...
 1.1.71: Here is a description from MINITAB of the strength data given in Ex...
 1.1.72: Anxiety disorders and symptoms can often be effectively treated wit...
 1.1.73: The article Can We Really Walk Straight? (Amer. J. of Physical Anth...
 1.1.74: The mode of a numerical data set is the value that occurs most freq...
 1.1.75: Specimens of three different types of rope wire were selected, and ...
 1.1.76: The three measures of center introduced in this chapter are the mea...
 1.1.77: Consider the following data on active repair time (hours) for a sam...
 1.1.78: Consider a sample x1, x2, . . . , xn and suppose that the values of...
 1.1.79: Let and denote the sample mean and variance for the sample x1, . . ...
 1.1.80: Lengths of bus routes for any particular transit system will typica...
 1.1.81: A study carried out to investigate the distribution of total brakin...
 1.1.82: The sample data x1, x2, . . . , xn sometimes represents a time seri...
 1.1.83: Consider numerical observations x1, . . . , xn. It is frequently of...
Solutions for Chapter 1: Overview and Descriptive Statistics
Full solutions for Probability and Statistics for Engineering and the Sciences (with Student Suite Online)  7th Edition
ISBN: 9780495382171
Solutions for Chapter 1: Overview and Descriptive Statistics
Get Full SolutionsSince 83 problems in chapter 1: Overview and Descriptive Statistics have been answered, more than 20955 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Probability and Statistics for Engineering and the Sciences (with Student Suite Online), edition: 7. This expansive textbook survival guide covers the following chapters and their solutions. Probability and Statistics for Engineering and the Sciences (with Student Suite Online) was written by and is associated to the ISBN: 9780495382171. Chapter 1: Overview and Descriptive Statistics includes 83 full stepbystep solutions.

Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

Bayes’ estimator
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

Biased estimator
Unbiased estimator.

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.

Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

Chisquare (or chisquared) random variable
A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

Comparative experiment
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

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 .

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

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

Density function
Another name for a probability density function

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

Dispersion
The amount of variability exhibited by data

Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

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.

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model