 10.101: Consider the hypothesis test against with known variances and Suppo...
 10.102: Consider the hypothesis test against with known variances and Suppo...
 10.103: Consider the hypothesis test against with known variances and Suppo...
 10.104: Two machines are used for filling plastic bottles with a net volume...
 10.105: Two types of plastic are suitable for use by an electronics compone...
 10.106: The burning rates of two different solidfuel propellants used in a...
 10.107: Two different formulations of an oxygenated motor fuel are being te...
 10.108: A polymer is manufactured in a batch chemical process. Viscosity me...
 10.109: The concentration of active ingredient in a liquid laundry detergen...
 10.1010: Consider the computer output below. TwoSample TTest and CI Sample...
 10.1011: Consider the computer output below. TwoSample TTest and Cl Sample...
 10.1012: Consider the hypothesis test against Suppose that sample sizes are ...
 10.1013: Consider the hypothesis test against Suppose that sample sizes and ...
 10.1014: Consider the hypothesis test against Suppose that sample sizes and ...
 10.1015: The diameter of steel rods manufactured on two different extrusion ...
 10.1016: An article in Fire Technology investigated two different foam expan...
 10.1017: Two catalysts may be used in a batch chemical process. Twelve batch...
 10.1018: The deflection temperature under load for two different types of pl...
 10.1019: In semiconductor manufacturing, wet chemical etching is often used ...
 10.1020: Two suppliers manufacture a plastic gear used in a laser printer. T...
 10.1021: The melting points of two alloys used in formulating solder were in...
 10.1022: A photoconductor film is manufactured at a nominal thickness of 25 ...
 10.1023: Two companies manufacture a rubber material intended for use in an ...
 10.1024: The thickness of a plastic film (in mils) on a substrate material i...
 10.1025: An article in Electronic Components and Technology Conference (2001...
 10.1026: An article in IEEE International Symposium on Electromagnetic Compa...
 10.1027: An article in Radio Engineering and Electronic Physics (1984, Vol. ...
 10.1028: An article in Technometrics (1999, Vol. 41, pp. 202211) studied the...
 10.1029: The overall distance traveled by a golf ball is tested by hitting t...
 10.1030: The springlike effect in a golf club could be determined by measur...
 10.1031: An electrical engineer must design a circuit to deliver the maximum...
 10.1032: One of the authors travels regularly to Seattle, Washington. He use...
 10.1033: The manufacturer of a hot tub is interested in testing two differen...
 10.1034: Consider the chemical etch rate data in Exercise 1019. (a) Use the...
 10.1035: Consider the pipe deflection data in Exercise 1018. (a) Use the Wi...
 10.1036: Consider the distance traveled by a golf ball in Exercise 1029. (a...
 10.1037: Consider the shear strength experiment described in Example 1010. ...
 10.1038: Consider the parking data in Example 1011. (a) Use the paired tte...
 10.1039: The manager of a fleet of automobiles is testing two brands of radi...
 10.1040: A computer scientist is investigating the usefulness of two differe...
 10.1041: Fifteen adult males between the ages of 35 and 50 participated in a...
 10.1042: An article in the Journal of Aircraft (Vol. 23, 1986, pp. 859864) d...
 10.1043: Ten individuals have participated in a dietmodification program to...
 10.1044: Two different analytical tests can be used to determine the impurit...
 10.1045: An article in Neurology (1998, Vol. 50, pp. 12461252) discussed tha...
 10.1046: In Biometrics (1990, Vol. 46, pp. 67387), the authors analyzed the ...
 10.1047: Use the sign test on the blood cholesterol data in Exercise 1041. ...
 10.1048: Repeat Exercise 1047 using the Wilcoxon signedrank test. State car...
 10.1049: For an F distribution, find the following: (a) f0.25,5,10 (b) f0.10...
 10.1050: For an F distribution, find the following: (a) f0.25,7,15 (b) f0.10...
 10.1051: Consider the hypothesis test H0 :2 1 2 2 against H1 :2 1 2 2. Suppo...
 10.1052: Consider the hypothesis test H0 :2 1 2 2 against H0 :2 1 2 2. Suppo...
 10.1053: Consider the hypothesis test H0 :2 1 2 2 against H1 :2 1 2 2. Suppo...
 10.1054: Two chemical companies can supply a raw material. The concentration...
 10.1055: A study was performed to determine whether men and women differ in ...
 10.1056: Consider the foam data in Exercise 1016. Construct the following: ...
 10.1057: Consider the diameter data in Exercise 1015. Construct the followi...
 10.1058: Consider the gear impact strength data in Exercise 1020. Is there ...
 10.1059: Consider the meltingpoint data in Exercise 1021. Do the sample da...
 10.1060: Exercise 1024 presented measurements of plastic coating thickness ...
 10.1061: Reconsider the overall distance data for golf balls in Exercise 10...
 10.1062: Reconsider the coefficient of restitution data in Exercise 1030. D...
 10.1063: Consider the weight of paper data from Technometrics in Exercise 10...
 10.1064: Consider the film speed data in Exercise 1022. (a) Test H0: 2 1 2 ...
 10.1065: Consider the etch rate data in Exercise 1019. (a) Test the hypothe...
 10.1066: Consider the computer output below. Test and Cl for Two Proportions...
 10.1067: Consider the computer output below. Test and CI for Two Proportions...
 10.1068: An article in Knee Surgery, Sports Traumatology, Arthroscopy (2005,...
 10.1069: In the 2004 presidential election, exit polls from the critical sta...
 10.1070: Two different types of injectionmolding machines are used to form ...
 10.1071: Two different types of polishing solutions are being evaluated for ...
 10.1072: A random sample of 500 adult residents of Maricopa County found tha...
 10.1073: Consider the computer output below. TwoSample TTest and Cl Sample...
 10.1074: Consider the computer output below. TwoSample TTest CI Sample N M...
 10.1075: An article in the Journal of Materials Engineering (1989, Vol. 11, ...
 10.1076: A procurement specialist has purchased 25 resistors from vendor 1 a...
 10.1077: A liquid dietary product implies in its advertising that use of the...
 10.1078: The breaking strength of yarn supplied by two manufacturers is bein...
 10.1079: The Salk polio vaccine experiment in 1954 focused on the effectiven...
 10.1080: Consider Supplemental Exercise 1078. Suppose that prior to collect...
 10.1081: A random sample of 1500 residential telephones in Phoenix in 1990 f...
 10.1082: In a random sample of 200 Phoenix residents who drive a domestic ca...
 10.1083: Consider the previous exercise, which summarized data collected fro...
 10.1084: A manufacturer of a new pain relief tablet would like to demonstrat...
 10.1085: Two machines are used to fill plastic bottles with dishwashing dete...
 10.1086: Suppose that we are testing H0: 1 2 versus H1 :1 2, and we plan to ...
 10.1087: Consider the situation described in Exercise 1071. (a) Redefine th...
 10.1088: Consider the firefighting foam expanding agents investigated in Ex...
 10.1089: A fueleconomy study was conducted for two German automobiles, Merc...
 10.1090: An experiment was conducted to compare the filling capability of pa...
 10.1091: A Rockwell hardnesstesting machine presses a tip into a test coupo...
 10.1092: Two different gauges can be used to measure the depth of bath mater...
 10.1093: An article in the Journal of the Environmental Engineering Division...
 10.1094: Three different pesticides can be used to control infestation of gr...
 10.1095: Suppose that we wish to test H0: 1 2 versus H1: 1 2, where 2 1 and ...
 10.1096: Suppose that we wish to test the hypothesis H0: 1 2 versus H1: 1 2,...
 10.1097: Suppose that we wish to test H0: 0 versus H1: 0, where the populati...
 10.1098: Construct a data set for which the paired ttest statistic is very ...
 10.1099: In some situations involving proportions, we are interested in the ...
 10.10100: Derive an expression for for the test of the equality of the varian...
Solutions for Chapter 10: Statistical Inference for Two Samples
Full solutions for Applied Statistics and Probability for Engineers  5th Edition
ISBN: 9780470053041
Solutions for Chapter 10: Statistical Inference for Two Samples
Get Full SolutionsApplied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780470053041. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers, edition: 5. Since 100 problems in chapter 10: Statistical Inference for Two Samples have been answered, more than 22387 students have viewed full stepbystep solutions from this chapter. Chapter 10: Statistical Inference for Two Samples includes 100 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions.

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

Addition rule
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

Assignable cause
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

Bayesâ€™ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Conidence level
Another term for the conidence coeficient.

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

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 coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Crossed factors
Another name for factors that are arranged in a factorial experiment.

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

Design matrix
A matrix that provides the tests that are to be conducted in an experiment.

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Estimate (or point estimate)
The numerical value of a point estimator.

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.

Extra sum of squares method
A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

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.

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