Montgomery · 2013
Design and Analysis of Experiments
- Matches
- Very close
- Close
- Differs
Factorial gives the book's answers. Where they differ, this page says why: some are misprints in the book, and for some the reason is not known yet.
Examples
Each example, and how closely Factorial gives its answers.
Pages 1 to 99
- Golf scores: type of driver by type of ball, a 2^2 factorial with two rounds at each combinationExample · pp. 4-6Matches
- The golf experiment's two-level factorial designs in three, four and ten factors, by their run countsDesign · pp. 6-7Matches
- One-half fraction of the four-factor golf experiment: driver, ball, beverage and mode of travel in 8 runsDesign · pp. 7-8Matches
- A web page of seven components with 4, 8, 6, 5, 4, 3 and 7 choices, as a full factorialDesign · p. 11Matches
- Tension bond strength of Portland cement mortar, modified with a polymer latex emulsion and unmodifiedExample · pp. 25-47Close
- Normalized fluorescence of nerve and of muscle tissue two hours after a fluorescently labelled peptide, 12 miceExample · pp. 48-50Very close
- Hardness readings of two tips on 10 metal specimens, each specimen divided in two and tested once with each tipExample · pp. 53-57Matches
- Etch rate of a single-wafer plasma etching tool at four levels of RF power, five wafers at eachExample · pp. 66-129Close
- Peak discharge of a watershed estimated by four methods, six estimates eachExample · pp. 85-88Not yet explained
Pages 100 to 199
- Total antioxidant capacity in blood after dark chocolate, dark chocolate with milk, and milk chocolateExample · pp. 110-112Matches
- Sales from three designs of end-aisle display, each tried in five storesExample · pp. 112-114Matches
- Cell voltage and its standard deviation (pot noise) under four ratio control algorithmsExample · pp. 114-116Matches
- Output of four looms chosen at random from a textile mill, four readings eachExample · pp. 116-124Matches
- Yield of vascular grafts at four extrusion pressures, in a randomized complete block design on six batches of resinExample · pp. 144-155Not yet explained
- Burning rate of five rocket propellant formulations in a 5 x 5 Latin square of batches and operators, then a Graeco-Latin square with test assembliesExample · pp. 158-167Matches
- Reaction time with four catalysts in a balanced incomplete block design on four batches of raw material, three catalysts in eachExample · pp. 168-176Not yet explained
- A two-factor factorial with one response at each corner, no interaction (Figure 5.1)Example · pp. 183-185Matches
- A two-factor factorial with one response at each corner, with interaction (Figure 5.2)Example · pp. 184-186Matches
- Life of batteries with three plate materials at three temperatures, a 3^2 factorial with four batteries at each combinationExample · pp. 187-214Close
Pages 200 to 299
- Impurity of a chemical product at three temperatures and five pressures, one observation per cellExample · pp. 203-205Very close
- Deviation from the target fill height of soft drink bottles: carbonation, operating pressure and line speed, a 3 x 2 x 2 factorial run twiceExample · pp. 208-211Very close
- Effective life of a cutting tool at three tool angles and three cutting speeds, a 3^2 factorial run twice (coded data)Example · pp. 214-219, 396-397Very close
- Intensity at which operators detect a target on a radar scope: three levels of ground clutter by two filter types, with the operators as blocksExample · pp. 220-223Not yet explained
- The radar detection experiment run as a 3 x 2 factorial in a 6 x 6 Latin square of days and operatorsExample · pp. 223-224Very close
- Yield of a chemical process: reactant concentration by amount of catalyst, a 2^2 factorial run three timesExample · pp. 234-241Close
- The 2^3 design matrix in the + and − notation, the treatment combinations (1) to abc, and the 0 and 1 notationDesign · pp. 241-242Matches
- Etch rate of silicon nitride: gap, C2F6 gas flow and RF power, a 2^3 factorial run twiceExample · pp. 245-253Not yet explained
- Filtration rate in a pilot plant: temperature, pressure, formaldehyde concentration and stirring rate, a single replicate of a 2^4Example · pp. 257-268Very close
- Advance rate of a drill: load, flow rate, rotational speed and type of mud, a single replicate of a 2^4 analysed in ln y (Daniel 1976)Example · pp. 269-271Close
- Defects in aircraft interior panels: temperature, clamp time, resin flow and closing time in a single replicate of a 2^4, for location and dispersionExample · pp. 271-274Differs
- Oxide thickness of wafers in a vertical oxidation furnace: temperature, time, pressure and gas flow, a 2^4 with four wafers measured in each runExample · pp. 274-278Misprint found
- Response rate to credit card offers: annual fee, account-opening fee, initial and long-term interest rate, a single replicate of a 2^4 mailed to 7500 customers a runExample · pp. 278-280Matches
- The 2^2 design in one replicate as an optimal design: D-, G- and I-optimality, and JMP's prediction variance outputDesign · pp. 281-285Very close
- The filtration 2^4 of Example 6.2 with four runs at the centre: a test for pure quadratic curvatureExample · pp. 286-288Matches
- Voltage across a DC circuit: current by resistance, a 2^2 run twice, analysed in coded and in engineering unitsExample · pp. 290-292Misprint found
Pages 300 to 399
- The chemical process 2^2 of Section 6.2 with each replicate run on its own batch of raw material: three blocksExample · p. 305Very close
- A 2^2 in two blocks of two runs, AB confounded with blocksDesign · pp. 306-307Matches
- A 2^3 in two blocks of four runs, ABC confounded with blocks: the table of signs, the defining contrast L = x1 + x2 + x3 and the principal blockDesign · pp. 307-309Matches
- The filtration 2^4 of Example 6.2 in two blocks of eight, ABCD confounded, with every response of the poorer batch 20 lowerExample · pp. 310-312Very close
- The filtration 2^4 of Example 6.2 run unblocked, the first eight runs in time 20 lower (Table 7.8)Example · pp. 312-313Not yet explained
- A 2^5 in four blocks of eight runs, ADE and BCE chosen and ABCD confounded with themDesign · pp. 313-315Matches
- A 2^6 in eight blocks of eight runs, ABEF, ABCD and ACE chosen to generate the blocksDesign · p. 315Matches
- Suggested blocking arrangements for the 2^k factorial in 2 to 64 blocks, k = 3 to 7 (Table 7.9)Design · p. 316Differs
- The plasma etch 2^3 of Example 6.1 run in two replicates of two shifts each, ABC confounded in replicate I and AB in replicate IIExample · p. 318Differs
- The two one-half fractions of the 2^3 design, I = ABC and I = −ABC, from the table of plus and minus signsDesign · pp. 321-325Matches
- Filtration rate: the one-half fraction I = ABCD of the pilot plant's 2^4, its runs taken from the full factorialExample · pp. 325-327, 333, 469Very close
- Yield of an integrated circuit process: aperture, exposure time, develop time, mask dimension and etch time in a 2^(5-1)Example · pp. 327-331Matches
- Filtration rate: the principal fraction of Example 8.1 and its alternate fraction I = −ABCD, together the full 2^4Example · p. 332Matches
- The 2^(6-2) resolution IV design with I = ABCE = BCDF: its construction, alias structure, alternate fraction and two blocksDesign · pp. 333-335, 344-345Matches
- Shrinkage of injection molded parts: mold temperature, screw speed, holding time, cycle time, gate size and holding pressure in a 2^(6-2)Example · pp. 336-340Close
- Three choices of generators for the 2^(7-2) resolution IV design, compared by their alias structures and word length patternsDesign · pp. 340-341Matches
- A selection of 2^(k-p) fractional factorial designs of the highest resolution, for 3 to 15 factors in up to 128 runsDesign · pp. 341-342Matches
- The 2^(7-3) resolution IV design for seven factors in 16 runs, and the 32-run 2^(7-2) it is compared withDesign · pp. 341-344Matches
- Profile deviation of jet engine impeller blades from a five-axis CNC machine: eight machine settings in a 2^(8-3) in four blocksExample · pp. 345-349Very close
- The alias matrix of the 2^(3-1) with I = ABC, for the main-effects model when the two-factor interactions are presentDesign · pp. 349-351Matches
- The saturated 2^(7-4) resolution III design for seven factors in eight runs, its alias structure, and a fold over on factor DDesign · pp. 351-354Matches
- The 2^(6-3) resolution III design: the 2^(7-4) of Table 8.19 with column G droppedDesign · pp. 352-353Matches
- Eye focus time: acuity, distance, target shape, illumination, target size, target density and subject in a 2^(7-4) and its full fold overExample · pp. 354-357Matches
- The 12-run Plackett-Burman design for 11 factors, written from the generating row of Table 8.23Design · pp. 357-358Misprint found
- The 20-run Plackett-Burman design for 19 factors, written from the generating row of Table 8.23Design · pp. 357-358Matches
- The 24-run Plackett-Burman design for 23 factors, written from the generating row of Table 8.23Design · pp. 357-358Matches
- The 36-run Plackett-Burman design for 35 factors, written from the generating row of Table 8.23Design · pp. 357-358Matches
- The 28-run Plackett-Burman design for 27 factors, written from the blocks of Table 8.23Design · pp. 357-358Matches
- A 20-run Plackett-Burman design in 12 factors, with responses simulated from a model of four main effects and two interactionsExample · pp. 360-366Misprint found
- A 2^(4-1) resolution IV design from the 2^(3-1) with I = ABC and its fold over, the identity column becoming factor DDesign · pp. 366-367Matches
- Useful factorial and fractional factorial designs of 4, 8, 16 and 32 runs: how many factors each type of design takesDesign · pp. 367, 375-376Matches
- Photoresist thickness on a spin coater: a 2^(6-2) resolution IV design and its single-factor fold over on spin speed, in two blocksExample · pp. 368-371Misprint found
- Photoresist thickness on a spin coater: the 2^(6-2) with a partial fold over, the eight fold-over runs with spin speed lowExample · pp. 371-373Matches
- The smallest two-level fractions of resolution at least V for five to eleven factorsDesign · pp. 373-374Matches
- A supersaturated design for ten factors in six runs, half of the 12-run Plackett-Burman design sorted by its last columnDesign · pp. 374-375Matches
- Colour of a chemical product: solvent/reactant, catalyst/reactant, temperature, reactant purity and reactant pH in a 2^(5-1) (Problem 8.9)Exercise · p. 376Matches
- Yield: condensation temperature, amount of material 1, solvent volume, condensation time and amount of material 2 in a 2^(5-2) (Problem 8.11)Exercise · p. 377Matches
- Average annual cost of a simulated inventory system: order quantity, reorder point, setup cost, backorder cost and carrying cost rate, a 2^(5-2) and two more fractions (Problem 8.23)Exercise · pp. 377-378Matches
- Camber of semiconductor substrates: lamination temperature, time and pressure and firing temperature, cycle time and dew point in 16 runs (Problem 8.28)Exercise · pp. 378-379Very close
- Resist thickness on a spin coater: volume, batch, spin time, spin speed, acceleration and cover in a 2^(6-1), three readings per wafer (Problem 8.29)Exercise · pp. 379-380Matches
- Ranks of 1985 Pinot Noir wines: clone, oak, barrel age, yeast/skin contact, stems, toast, whole cluster and fermentation temperature in a 2^(8-4) (Problem 8.30)Exercise · pp. 379-381Matches
- Si/SiGe selective epitaxial growth: SiH2Cl2, GeH4, HCl, B2H6 and temperature in a 2^(5-1) with two centre runs, three responses (Problem 8.36)Exercise · pp. 382-383Matches
- Solder paste printing: squeegee pressure, printing speed, squeegee angle, temperature, viscosity, cleaning interval, separation speed and humidity in a 2^(8-3) (Problem 8.37)Exercise · pp. 383-384Matches
- Response rate of a direct mail credit card offer: 19 factors of the envelope, letter and offer in a 20-run Plackett-Burman design (Problem 8.38)Exercise · pp. 385-386Matches
- Proportion of nondefective sand castings of engine intake manifolds: ten factors in a 16-run resolution III fraction (Problem 8.50)Exercise · pp. 389-390Very close
- Defects in the finish of sheet-molded grill opening panels: nine factors in a 16-run resolution III fraction (Problem 8.51)Exercise · pp. 390-391Very close
- Transistor gain: six factors in a 2^(6-2) resolution IV design (Problem 8.52)Exercise · p. 391Matches
- Thickness of the carbonized layer on gear teeth: furnace temperature, cycle time, carbon concentration and cycle durations in a 2^(6-2) (Problem 8.53)Exercise · pp. 391-392Matches
- Syrup loss from frothing when filling 5-gallon containers: three nozzles, filling speeds and pressures, a 3^3 factorial run twice (coded data)Example · pp. 398-402Very close
Pages 400 to 499
- A single replicate of the 3^2 design in three blocks with the AB² component of interaction confoundedExample · pp. 403-404Matches
- The 3^3 design in three blocks of nine runs with the AB²C² component of the three-factor interaction confoundedDesign · pp. 405-406Matches
- The 3^4 design in nine blocks of nine runs with ABC and AB²D², and their generalized interactions AC²D and BC²D², confoundedDesign · pp. 406-407Misprint found
- The 3^7 design in 27 blocks of 81 runs: three components of interaction chosen, and their ten generalized interactionsDesign · p. 407Matches
- The three one-third fractions of the 3^3 design with defining relation I = AB²C², each a 3^(3−1) of resolution IIIDesign · pp. 408-409Matches
- A 3^(4−1) fractional factorial of resolution IV with I = AB²CD, made by setting x4 = 2x1 + x2 + 2x3 (mod 3) in a full 3^3Design · p. 410Matches
- A 3^(4−2) fractional factorial of resolution III with I = AB²C = BCD = AC²D = ABD², and its alias structureDesign · pp. 410-411Matches
- A two-level factor A and a three-level factor X in the eight runs of the 2^3, X made from the columns B and CDesign · pp. 412-413Matches
- A four-level factor X, made from the columns A and B, and two two-level factors C and D in the 16 runs of the 2^4Design · pp. 414-415Matches
- The Hall I design: one of Hall's five nonisomorphic orthogonal designs for 15 two-level factors in 16 runsDesign · p. 418Matches
- The Hall II design: one of Hall's five nonisomorphic orthogonal designs for 15 two-level factors in 16 runsDesign · pp. 418-419Misprint found
- The Hall III design: one of Hall's five nonisomorphic orthogonal designs for 15 two-level factors in 16 runsDesign · p. 419Misprint found
- The Hall IV design: one of Hall's five nonisomorphic orthogonal designs for 15 two-level factors in 16 runsDesign · p. 419Misprint found
- The Hall V design: one of Hall's five nonisomorphic orthogonal designs for 15 two-level factors in 16 runsDesign · p. 420Matches
- The recommended nonregular orthogonal design for 6 two-level factors in 16 runs, which confounds no two of its main effects and two-factor interactionsDesign · pp. 421-422Matches
- The recommended nonregular orthogonal design for 7 two-level factors in 16 runs, which confounds no two of its main effects and two-factor interactionsDesign · pp. 421-422Very close
- The recommended nonregular orthogonal design for 8 two-level factors in 16 runs, which confounds no two of its main effects and two-factor interactionsDesign · p. 422Misprint found
- Photoresist thickness in the spin coating experiment, simulated on the six-factor no-confounding design and analysed by forward stepwise regressionExample · pp. 424-425Matches
- The recommended 16-run nonregular design for 9 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 426Matches
- The recommended 16-run nonregular design for 10 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 427Matches
- The recommended 16-run nonregular design for 11 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 428Matches
- The recommended 16-run nonregular design for 12 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 429Matches
- The recommended 16-run nonregular design for 13 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 430Matches
- The recommended 16-run nonregular design for 14 two-level factors, which confounds no main effect with a two-factor interactionDesign · p. 431Matches
- The 9-run D-optimal design for the main effects of two three-level categorical factors, a 3^2 factorialDesign · pp. 433-434Matches
- The 9-run I-optimal design for the main effects of two three-level categorical factors, the same 3^2 factorialDesign · pp. 433-434Matches
- The 12-run D-optimal design for two three-level categorical factors and their interaction: the 3^2 with three runs replicatedDesign · p. 434Matches
- The 12-run I-optimal design for two three-level categorical factors and their interaction: the 3^2 with three runs replicatedDesign · p. 434Misprint found
- A 12-run I-optimal screening design for six continuous factors in four blocks (days) of three runsDesign · p. 435Matches
- An 18-run minimum-run resolution IV design for nine factors, a D-optimal nonregular fraction, and its partial aliasing of two-factor interactionsDesign · pp. 435-437Matches
- A 12-run resolution IV design for six factors, and its partial aliasing of two-factor interactionsDesign · p. 437Matches
- A 22-run nonregular resolution V fraction for six factors, the fewest runs that fit every main effect and two-factor interactionDesign · p. 438Matches
- A 38-run nonregular resolution V fraction for eight factorsDesign · pp. 438-439Matches
- A 24-run D-optimal design for two three-level categorical factors and one two-level factor, all main effects and two-factor interactionsDesign · pp. 440-441Matches
- A 14-run D-optimal design, the minimum, for two three-level categorical factors and one two-level factor with all two-factor interactionsDesign · pp. 440-442Matches
- A 15-run D-optimal main-effects design for categorical factors of five, four and three levels and two two-level factorsDesign · pp. 441-443Matches
- Yield of a chemical process at three temperatures and three pressures, a 3^2 run twice (Problem 9.6)Exercise · p. 445Matches
- Viscosity of a polymer against reaction temperature and catalyst feed rate: a multiple linear regression on 16 observationsExample · pp. 454-473Very close
- Yield of a chemical process: a 2^3 factorial in temperature, pressure and catalyst concentration with four centre runs, fitted by regressionExample · pp. 457-459Very close
- Yield of a chemical process from a 2^3 with four centre runs whose factor levels were not held where the design set them, fitted by regressionExample · pp. 460-461Very close
- De-aliasing AB and CD of the 2^(4−1) with I = ABCD by adding one run, or four in a block of their ownDesign · pp. 461-462Matches
- The yield of a chemical process against reaction time and temperature: a 2^2 with five centre runs, a first-order model and its path of steepest ascentExample · pp. 481-486Very close
- The yields observed at twelve steps along the path of steepest ascent of Example 11.1Example · p. 484Matches
- The yield, viscosity and molecular weight of Example 11.1's process in a central composite design about 85 minutes and 175°FExample · pp. 485-500Not yet explained
Pages 500 to 599
- A Box-Behnken design for three factors, twelve edge midpoints and three centre runsDesign · pp. 503-504Matches
- A small composite design for three factors: a half fraction of the 2^3, six axial runs at 1.73 and four centre runsDesign · pp. 505-506Matches
- A hybrid design for three factors in eleven runsDesign · p. 506Matches
- A rotatable central composite design in two factors run in two blocks that block orthogonallyDesign · pp. 507-510Matches
- Rotatable and near-rotatable central composite designs in two to seven factors that block orthogonallyDesign · pp. 510-511Misprint found
- Three twelve-run designs for a second-order model in the adhesive's constrained region −1.5 ≤ x1 + x2 ≤ 1: an inscribed CCD, a D-optimal design and the D-optimal design with two runs moved to its centreDesign · pp. 511-517Very close
- JMP's 16-run D-optimal design for a second-order model in four factors on a cubeDesign · pp. 517-520Matches
- JMP's 16-run I-optimal design for a second-order model in four factors on a cubeDesign · pp. 517-520Matches
- Jones and Nachtsheim's definitive screening design for 4 factors in 9 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 5 factors in 11 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 6 factors in 13 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 7 factors in 15 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 8 factors in 17 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 9 factors in 19 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 10 factors in 21 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 11 factors in 23 runsDesign · pp. 520-522Matches
- Jones and Nachtsheim's definitive screening design for 12 factors in 25 runsDesign · pp. 520-522Misprint found
- The conference matrix of order 6, from which the 13-run definitive screening design for six factors is madeDesign · p. 522Matches
- The temperature in a jet engine's exhaust plume from a computational fluid dynamics model, at ten points of a sphere-packing designExample · pp. 528-530Matches
- Yarn elongation for blends of polyethylene, polystyrene and polypropylene in a {3, 2} simplex lattice (Cornell 2002)Example · pp. 533-534Matches
- The {3, 2} simplex lattice augmented with the overall centroid and three axial check blendsDesign · pp. 534-535Matches
- Knoop hardness and percent solids of an automotive clear coat: a 14-run D-optimal design over the constrained mixture of monomer, crosslinker and resinExample · pp. 536-539Misprint found
- Evolutionary operation of a chemical process: three cycles of a 2^2 with a centre point in temperature and pressureExample · pp. 540-544Misprint found
- A central composite design in three factors and three blocks: two half fractions of the cube with two centre runs each, and the axial runs at 1.633 with two (Problem 11.18)Design · p. 548Matches
- Free height of leaf springs: a 2^(4−1) inner array in the controllable factors crossed with quench oil temperature, the noise factor, and its mean and ln(s²) modelsExample · pp. 556-560Matches
- Pull-off force of an elastomeric connector on a nylon tube: a 3^(4−2) inner array crossed with a 2^3 outer array in three conditioning factors (Byrne and Taguchi 1987)Example · pp. 557-558Matches
- The outer array of the connector pull-off force experiment: a 2^3 in conditioning time, temperature and relative humidity, as printedDesign · pp. 557-558Misprint found
- The filtration 2^4 of Example 6.2 as a combined array: temperature a noise factor, its response, mean and variance modelsExample · pp. 562-565Very close
- A semiconductor process with two controllable and three noise variables: a 23-run combined array from a CCD in five factors, and its mean and variance modelsExample · pp. 565-566Very close
- Design-Expert's two-level resolution V design in seven factors and 30 runsDesign · pp. 567-568Matches
- Design-Expert's 23-run D-optimal design for three controllable and four noise variablesDesign · p. 568Matches
- Design-Expert's 18-run D-optimal design for a second-order response model in three controllable and two noise variablesDesign · p. 569Matches
- The filtration 2^4 of Example 6.2 without pressure: two replicates of a 2^3, temperature (A) a noise variable (Problem 12.9)Exercise · p. 570Differs
- Carbon monoxide emission against ethanol and air/fuel ratio in a 3^2 run twice (Hunter 1989) (Problem 12.10)Exercise · pp. 570-571Matches
- Carbon monoxide emission as if run in a 3^(4−2) fraction in four factors, the data of part (a) unchanged (Problem 12.10(b))Exercise · pp. 571-572Misprint found
- A gauge capability study: twenty parts measured twice by each of three operators, analysed with parts and operators random, and with operators fixedExample · pp. 575-586Close
- Pressure drop across a turbine's expansion valve against gas temperature (fixed), operator and pressure gauge (random), two replicates: exact, approximate and synthesized tests and the variance componentsExample · pp. 593-601Very close
Pages 600 to 699
- Purity of raw material from three suppliers, four batches from each and three determinations a batch: a two-stage nested designExample · pp. 605-613Matches
- Assembly time of hand-inserted components on circuit boards against three fixtures and two layouts, four operators within each layout, two replicates: a nested-factorial designExample · pp. 616-620Differs
- Tensile strength of paper against three pulp preparation methods and four cooking temperatures, three replicates: a split-plot design with the methods in the whole plotsExample · pp. 621-625Very close
- Oxide growth on silicon wafers: a 2^4 in two replicates, temperature and gas flow (hard to change) in the whole plots, time and wafer position in the subplotsDesign · pp. 627-628Matches
- Uniformity of a single-wafer plasma etch: a 2^(5-1) split-plot with electrode gap, gas flow and pressure (hard to change) in eight whole plots, time and RF power in the subplotsExample · pp. 628-632Misprint found
- JMP's default split-plot design for the plasma etching experiment: a 2^5 in eight whole plots of A, B and C, four subplots of D and E in eachDesign · pp. 632-633Matches
- Peak discharge of a watershed estimated by four methods: the Box-Cox choice of a power transformationExample · pp. 643-645Differs
- Coupons redeemed of 1000 mailed in each cell of a 2^3 in coupon value, time valid and ease of use: logistic regressionExample · pp. 647-648Matches
- Defects on sheet-molded grill opening panels: least squares on Freeman and Tukey's square root against a Poisson generalized linear modelExample · pp. 649-650Differs
- Cycles to failure of worsted yarn in a 3^3 in length, amplitude and load: least squares on ln(y) against a gamma generalized linear modelExample · pp. 650-651Not yet explained
- Battery life against three plate materials and three temperatures, with numbers of runs in the cells proportional to the row and column totalsExample · pp. 652-653Very close
- Breaking strength of monofilament fibre from three machines, with the fibre's diameter as a covariate: the analysis of covarianceExample · pp. 656-665Very close
- A 2^3 in two replicates with a covariate: no covariate, a common slope, and slopes that differ with the factorsExample · pp. 667-673Misprint found
- Viscosity and molecular weight of forty raw material samples available for a twenty-run experiment, the twenty chosen starredDesign · pp. 674-676Misprint found
- JMP's 20-run D-optimal design in two factors, X3 and X4, choosing twenty of forty raw material samples by their viscosity and molecular weightDesign · pp. 674-677Misprint found
Pages 700 to 799
- Alias relationships of the 2^(3-1) fraction of resolution III: 3 factors in 4 runsDesign · p. 706Matches
- Alias relationships of the 2^(4-1) fraction of resolution IV: 4 factors in 8 runsDesign · p. 706Matches
- Alias relationships of the 2^(5-2) fraction of resolution III: 5 factors in 8 runsDesign · p. 706Matches
- Alias relationships of the 2^(5-1) fraction of resolution V: 5 factors in 16 runsDesign · p. 706Matches
- Alias relationships of the 2^(6-3) fraction of resolution III: 6 factors in 8 runsDesign · p. 707Matches
- Alias relationships of the 2^(6-2) fraction of resolution IV: 6 factors in 16 runsDesign · p. 707Matches
- Alias relationships of the 2^(6-1) fraction of resolution VI: 6 factors in 32 runsDesign · p. 707Matches
- Alias relationships of the 2^(7-4) fraction of resolution III: 7 factors in 8 runsDesign · p. 708Matches
- Alias relationships of the 2^(7-3) fraction of resolution IV: 7 factors in 16 runsDesign · p. 708Matches
- Alias relationships of the 2^(7-2) fraction of resolution IV: 7 factors in 32 runsDesign · p. 708Matches
- Alias relationships of the 2^(7-1) fraction of resolution VII: 7 factors in 64 runsDesign · p. 708Matches
- Alias relationships of the 2^(8-4) fraction of resolution IV: 8 factors in 16 runsDesign · p. 709Matches
- Alias relationships of the 2^(8-3) fraction of resolution IV: 8 factors in 32 runsDesign · p. 709Matches
- Alias relationships of the 2^(8-2) fraction of resolution V: 8 factors in 64 runsDesign · p. 710Matches
- Alias relationships of the 2^(9-5) fraction of resolution III: 9 factors in 16 runsDesign · p. 710Matches
- Alias relationships of the 2^(9-4) fraction of resolution IV: 9 factors in 32 runsDesign · p. 711Matches
- Alias relationships of the 2^(9-3) fraction of resolution IV: 9 factors in 64 runsDesign · p. 711Matches
- Alias relationships of the 2^(10-6) fraction of resolution III: 10 factors in 16 runsDesign · p. 712Misprint found
- Alias relationships of the 2^(10-5) fraction of resolution IV: 10 factors in 32 runsDesign · p. 712Matches
- Alias relationships of the 2^(10-4) fraction of resolution IV: 10 factors in 64 runsDesign · p. 713Matches
- Alias relationships of the 2^(11-7) fraction of resolution III: 11 factors in 16 runsDesign · p. 714Matches
- Alias relationships of the 2^(11-6) fraction of resolution IV: 11 factors in 32 runsDesign · p. 715Matches
- Alias relationships of the 2^(12-8) fraction of resolution III: 12 factors in 16 runsDesign · p. 716Matches
- Alias relationships of the 2^(13-9) fraction of resolution III: 13 factors in 16 runsDesign · p. 716Matches
- Alias relationships of the 2^(14-10) fraction of resolution III: 14 factors in 16 runsDesign · p. 717Matches
- Alias relationships of the 2^(15-11) fraction of resolution III: 15 factors in 16 runsDesign · p. 717Misprint found
Misprints
Misprints found in the book, by page. Each shows what the book prints and what its own data give.
Anova f: Methods, √yp. 88
Book 76.99Data 81.05
F is 81.05 for 20 error degrees of freedom; the table divides the error sum of squares by 19, 10.8947/0.1415 = 76.99
Residual df: √yp. 88
Book 19Data 20
24 readings in 4 groups leave 20 error degrees of freedom, as Table 3.8 has; the table prints 19 and a total of 22
Ms residual: √yp. 88
Book 0.1415Data 0.1344
2.6884/20 = 0.1344; the table divides by 19
Std error: treatment meanp. 91
Book 8.13Data 8.17
A misprint: MSE is 333.70, and √(333.70/5) = 8.17, as Design-Expert prints in Figure 3.12
Ss residual: Pure Errorp. 103
Book 5338.20Data 5339.20
A misprint for 5339.20, which Table 3.4 prints and 16 × 333.70 confirms
Show the rest
Residual: standard order 9p. 196
Book 26.00Data -6.00
A misprint for −6.00: the run is 138 and its cell's mean 144.00, as Table 5.6 prints, and the Student residual −0.267 beside it is that of −6.00
Coefficient: material 2, Temp²p. 213
Book 0.41627Data -0.00566
The quadratic through material 2's cell means has a quadratic coefficient of -0.0056612 per °F²; the printed 0.41627 would bend the curve of Figure 5.18 far outside the data
Coefficient: material 3, Temp²p. 213
Book -0.43218Data -0.01025
The quadratic through material 3's cell means has a quadratic coefficient of -0.010248 per °F²; the printed -0.43218 would bend the curve of Figure 5.18 far outside the data
Coefficient: BC, coded equationp. 249
Book +1.06Data -1.0625
The BC coefficient is −1.06, as the table of coefficients above the equation prints it; the equation drops its sign
Ci high: A-Gapp. 250
Book 28.10Data -28.10
The upper limit is −28.10: the interval −50.81 ± 22.71 lies below zero, as the lower limit −73.52 and the coefficient's t of −4.88 say; the sign is dropped
Anova p: Cp. 260
Book <0.0001Data 0.00312441
The P-value of F = 17.38 on 1 and 8 degrees of freedom is 0.0031, not below 0.0001
Anova p: Dp. 260
Book <0.0001Data 0.000266595
The P-value of F = 38.13 on 1 and 8 degrees of freedom is 0.0003, not below 0.0001
Fitted: (1)p. 260
Book 46.22Data 46.25
The prediction is 46.25, as the next page and its table print it: 70.0625 − 10.8125 − 4.9375 − 7.3125 − 9.0625 + 8.3125
Coefficient: Intercept at x4 = 1p. 262
Book 77.3725Data 77.3750
The intercept with stirring rate at its high level is 70.0625 + 7.3125 = 77.375
Coefficient: Intercept at x1 = 1p. 262
Book 80.8725Data 80.8750
The intercept with temperature at its high level is 70.0625 + 10.8125 = 80.875
Residual std dev: B lowp. 272
Book 0.83Data 0.82
The standard deviation of the eight residuals at B − (−0.94, −0.69, −1.19, 0.56, 0.06, 0.81, −0.69, −1.44) is 0.82
Residual std dev: B −p. 273
Book 0.83Data 0.82
The standard deviation of the eight residuals at B − (−0.94, −0.69, −1.19, 0.56, 0.06, 0.81, −0.69, −1.44) is 0.82
Anova sum sq: ACp. 276
Book 451.46Data 451.56
The sum of squares is 451.56, as the mean square beside it on one degree of freedom says (Table 6.19: 451.563); a misprint
Df model: interaction onlyp. 292
Book 3Data 1
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has 1 degree of freedom for regression
Ss regression: interaction onlyp. 292
Book 71.267Data 71.244
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has a residual sum of squares of 0.1103, so 71.244 of the corrected total
Ms regression: interaction onlyp. 292
Book 23.756Data 71.244
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has one degree of freedom for regression
F regression: interaction onlyp. 292
Book 1085.95Data 4521.91
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has 1 and 7 degrees of freedom
Residual df: interaction onlyp. 292
Book 4Data 7
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has 7 residual degrees of freedom
Ss residual: interaction onlyp. 292
Book 0.088Data 0.110
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has a residual sum of squares of 0.1103, 7 × 0.1255²
Ms residual: interaction onlyp. 292
Book 0.022Data 0.016
Table 6.28 repeats the analysis of variance of Table 6.26; the one-term model through the origin has a residual mean square of 0.0158, 0.1255²
Block confounding: k = 7, 8 blocks of 16p. 316
Book ABC, DEF, AFG, ABCDEF, BCFG, ADEG, BCDEGData ABCD, ABEF, CDEF, ACEG, BDEG, BCFG, ADFG
The column prints the generalized interactions of ABC, DEF and AFG; those of the chosen ABCD, CDEF and ADFG are ABCD, CDEF, ADFG, ABEF, BCFG, ACEG and BDEG, seven four-factor interactions
Block confounding: k = 7, 8 blocks of 16p. 316
Book ABC, DEF, AFG, ABCDEF, BCFG, ADEG, BCDEGData ABCD, ABEF, ACEG, ADFG, BCFG, BDEG, CDEF
The column prints the generalized interactions of ABC, DEF and AFG; those of the chosen ABCD, CDEF and ADFG are ABCD, CDEF, ADFG, ABEF, BCFG, ACEG and BDEG, seven four-factor interactions
Anova f: Ap. 318
Book 16.20Data 16.19
The F ratio on the error mean square 2550.9625 is a little smaller; the table divides by its own 2550.4625, which inherits the slips in C and AC
Anova sum sq: Cp. 318
Book 374,850.5625Data 374850.0000
The sum of squares of C is 374,850.0625, as Tables 6.5 and 6.6 print it for the same sixteen runs; the table carries its 374,850.5625 into its error sum of squares
Anova mean sq: Cp. 318
Book 374,850.5625Data 374850.0000
The mean square of C is 374,850.0625; the slip of its sum of squares
Anova f: Cp. 318
Book 146.97Data 146.94
The F ratio on the error mean square 2550.9625 is a little smaller; the table divides by its own 2550.4625, which inherits the slips in C and AC
Anova sum sq: ACp. 318
Book 94,404.5625Data 94402.6000
The sum of squares of AC is 94,402.5625, as Tables 6.5 and 6.6 print it for the same sixteen runs; the table carries its 94,404.5625 into its error sum of squares
Anova mean sq: ACp. 318
Book 94,404.5625Data 94402.6000
The mean square of AC is 94,402.5625; the slip of its sum of squares
Anova p: ACp. 318
Book <0.001Data 0.00173551
The P-value of F = 37.01 on 1 and 5 degrees of freedom is 0.0017, not below 0.001
Ss residualp. 318
Book 12,752.3125Data 12754.8000
The error sum of squares is 12,754.8125; the table takes the total less its rows, and its rows for C and AC are 0.5 and 2 too large
Ms residualp. 318
Book 2550.4625Data 2550.9600
The error mean square is 2550.9625, 12,754.8125/5; the table's error sum of squares is 2.5 too small
Column: BD = CEp. 339
Book BD = CEData not in runs 2, 4, 6, 8, 9, 11, 13, 15
The column holds the signs of BD and of CF, its aliases in Table 8.8; CE is aliased with AB, the third column
Alias matrix: A, BDp. 358
Book -1 / 3Data 0.333333
In the design of Table 8.24 the weights of BD and BE in A's alias chain are +1/3 and that of BF −1/3, the sum over the runs of A times the interaction's column over 12; the text prints the opposite signs for these three, and agrees with the table for BC and KL
Alias matrix: A, BEp. 358
Book -1 / 3Data 0.333333
In the design of Table 8.24 the weights of BD and BE in A's alias chain are +1/3 and that of BF −1/3, the sum over the runs of A times the interaction's column over 12; the text prints the opposite signs for these three, and agrees with the table for BC and KL
Alias matrix: A, BFp. 358
Book 1 / 3Data -0.333333
In the design of Table 8.24 the weights of BD and BE in A's alias chain are +1/3 and that of BF −1/3, the sum over the runs of A times the interaction's column over 12; the text prints the opposite signs for these three, and agrees with the table for BC and KL
Alias matrix: X5 row, X3X4 columnp. 361
Book 0Data 0.2
The entry is the J-characteristic of X3, X4 and X5 over 20, which in this design can only be ±4/20 or ±12/20; it is 4/20 = 0.2, as X3's row prints for X4X5 and X4's for X3X5, which are the same product of columns
Largest effect: initial runs, Ap. 369
Book 152.81Data 158.12
The axis ends at the largest effect, as those of Figures 8.26 and 8.27 do; the largest of the sixteen runs of Table 8.31 is A's, 158.125, as Figure 8.27's axis has it for the partial fold over. 152.81 is the largest effect of the 32 runs of Table 8.32 (Figure 8.26)
Coefficient: nozzle 2, intercept, codedp. 400
Book 25.6Data -17.8
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, x1, codedp. 400
Book −22.8Data -5.08333
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, x1², codedp. 400
Book 14.1Data 84.2
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, x2², codedp. 400
Book −56.9Data -60.25
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, intercept, naturalp. 400
Book 180.1Data 2526.7
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, S, naturalp. 400
Book −9.475Data -50.6917
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, P, naturalp. 400
Book 66.75Data 70.75
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, S², naturalp. 400
Book 0.035Data 0.211
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Coefficient: nozzle 2, P², naturalp. 400
Book −2.2767Data -2.41
The least squares fit to nozzle 2's eighteen runs of Table 9.1 is ŷ = −17.8 − 5.1x1 − 12.3x2 + 84.3x1² − 60.3x2² − 0.8x1x2, and in the natural units ŷ = 2526.7 − 50.692S + 70.75P + 0.21063S² − 2.41P² − 0.0075SP; the printed models agree with it in x2, x1x2 and SP only. They agree in every term with a fit in which the means of the middle pressure, at the three speeds, are about 67, 87.5 and −49.6 in place of the table's 87.5, −49.5 and 77: two of the three means one speed to the right, as if a row of nozzle 2's data were shifted by a column in the fit
Component ss: ABC² = Y(ABC)p. 402
Book 18.77Data 584.11
By the book's rule ABC² groups the runs by x1 + x2 + 2x3 (mod 3), whose totals are 138, 4 and 23 and whose sum of squares is 584.11; the totals 63, 62 and 40, and 18.778 from them (which the book cuts to 18.77), are ABC's: the book lists the J(AB) totals in the reverse order of the I(AB) totals (u = 2, 1, 0), which exchanges the I and J diagonals of its display of J(AB) with C
Component ss: ABC = Z(ABC)p. 402
Book 584.11Data 18.78
ABC groups the runs by x1 + x2 + x3 (mod 3), whose totals are 40, 62 and 63 and whose sum of squares is 18.78; 584.11 is ABC²'s: the book lists the J(AB) totals in the reverse order of the I(AB) totals (u = 2, 1, 0), which exchanges the I and J diagonals of its display of J(AB) with C
Contrast values: block 6p. 407
Book (1,6)Data (1, 0)
Every run of block 6 has L1 = 1 and L2 = 0; a value modulo 3 is 0, 1 or 2, so (1,6) misprints (1,0), the one pair no other block has
Orthogonal: the fifteen columnsp. 418
Book 1Data 1.3
Run 6 prints 1 in column G; with −1 there, and run 12 restored as the row that completes the design, each column is balanced and every pair of the fifteen columns is orthogonal. The columns D, E, H, K, M and Q that Table 9.20 takes do not change, and Table 9.20's run 12 is the restored run's
Orthogonal: the fifteen columnsp. 419
Book 1Data 1.3
Run 16 prints 1 in column N; with −1 there each column is balanced and every pair of the fifteen columns is orthogonal
Orthogonal: the fifteen columnsp. 419
Book 1Data 1.3
Run 11 prints 1 in column H; with −1 there each column is balanced and every pair of the fifteen columns is orthogonal, and Table 9.22, whose column E is Hall IV's H, has −1 in run 11
Projection: columns of Hall IIIp. 420
Book A, B, D, H, J, M, and QData not in runs 5, 6, 7, 8, 9, 10, 15, 16
The fifth column of Table 9.21 is Hall III's K: its J differs in eight runs
Projection: columns of Hall IVp. 420
Book A, B, D, F, H, J, M, and OData not in runs 5, 6, 7, 8, 9, 11, 13, 15
Table 9.22's sixth column is Hall IV's K, not J, and its eighth is P: Hall's designs have no column O
Count: L1 in X2p. 434
Book 3Data 4
Table 9.35's column X2 holds L1 four times (runs 3, 4, 5 and 11) and L3 three times (runs 1, 7 and 9); the text exchanges the two counts
Count: L3 in X2p. 434
Book 4Data 3
Table 9.35's column X2 holds L1 four times (runs 3, 4, 5 and 11) and L3 three times (runs 1, 7 and 9); the text exchanges the two counts
Coefficient: least squares estimate, run 8 missing, Interceptp. 459
Book 51.25Data 51.06
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: least squares estimate, run 8 missing, temperaturep. 459
Book 5.75Data 5.71
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: least squares estimate, run 8 missing, pressurep. 459
Book 10.75Data 10.71
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: least squares estimate, run 8 missing, concentrationp. 459
Book 1.25Data 1.21
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: fitted model, run 8 missing, Interceptp. 459
Book 51.25Data 51.06
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: fitted model, run 8 missing, temperaturep. 459
Book 5.75Data 5.71
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: fitted model, run 8 missing, pressurep. 459
Book 10.75Data 10.71
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
Coefficient: fitted model, run 8 missing, concentrationp. 459
Book 1.25Data 1.21
The product of the printed (X'X)^-1 and X'y, and the least squares fit to the eleven runs, is β̂ = (51.058, 5.712, 10.712, 1.212): 51.058 = (5/52)(544) + (1/52)(−23 + 17 − 59). The printed estimates are each 1/8 to 1/4 above the fit
(X'X)^-1: (X'X)^-1 [3, 4]p. 461
Book 4.37851e-3Data 0.0043729
The book inverts X'X as printed, its entries rounded to four decimals, which gives 4.37351 × 10^−3, and prints it as 4.37851; the X'X of the coded levels gives 4.37290 × 10^−3
(X'X)^-1: (X'X)^-1 [4, 3]p. 461
Book 4.37851e-3Data 0.0043729
The book inverts X'X as printed, its entries rounded to four decimals, which gives 4.37351 × 10^−3, and prints it as 4.37851; the X'X of the coded levels gives 4.37290 × 10^−3
Path ξ2: step 11p. 484
Book 179Data 178
The book adds 2°F a step, the step of 2.10°F rounded; on the path the temperature after 11 steps is 178.06°F; 2°F a step would give 177°F, so 179 is a misprint as well
Path ξ2: step 12p. 484
Book 181Data 180
The book adds 2°F a step, the step of 2.10°F rounded; on the path the temperature after 12 steps is 180.16°F; 2°F a step would give 179°F, so 181 is a misprint as well
M': w2 on x1p. 494
Book 0.9574Data 0.9571
−0.9571, M12 as the book prints it above; −0.9574 is a misprint
W equation: w1 on x1p. 495
Book 0.2897Data 0.2898
0.2898 to four decimals (0.28978), as M prints it; the equation's 0.2897 is a misprint
W equation: w2 on x2p. 495
Book 0.2888Data 0.2898
0.2898 to four decimals, as M prints it; 0.2888 is a misprint
N: k = 7, ½ Rep.p. 511
Book 80Data 90
The blocks hold 8 × 9 + 18 = 90 runs, as the library's design with 12 centre runs has; 80 is a misprint
Conference matrix: m = 12p. 522
Book constructed from a conference matrixData no relabelling of the library's columns gives the printed runs
The printed design is not the library's, made from a conference matrix of order 12, in any order or sign of its columns: its main effects are not orthogonal, ten pairs of columns having x_i'x_j = ±4
Linear mixture ms: Linear Mixturep. 538
Book 1465.66Data 1465.55
2931.09/2 = 1465.55; the table's 1465.66 is a misprint
Effect: cycle 1, change in meanp. 541
Book 0.02Data -0.02
(84.2 + 84.9 + 84.5 + 84.3 − 4 × 84.5)/5 = −0.02; the sheet prints it without its minus sign
Effect: information board, Change in meanp. 543
Book 0.07Data -0.07
The change in mean is −0.07, as Table 11.25 prints it; the board drops its sign
New centre: point (3), temperaturep. 543
Book 3Data 0
Point (3) is run at 255°F and 150 psi in each cycle (Figure 11.49); no run is at 225°F, a misprint for 255°F
Distinct runs: Table 12.2's outer arrayp. 557
Book 8Data 7
The sixth column prints G as −, the fifth's setting; a 2^3 needs + there, as the pattern − + − + of the other columns has it
Mean: C, D run 1p. 570
Book 57.75Data 57.25
The four readings 45, 48, 71 and 65 (Example 6.2's runs (1), b, a and ab) average 57.25
Alias weight: β11 on β34p. 572
Book 0Data 1
The alias matrix gives β11's estimate the weight +1 on β34 as well: E(β̂11) = β11 − (β23 − β24)/2 + β34, as β33's and β44's carry β14 and β13
P: ABp. 594
Book 0.01Data 0.00
The P-value of F = 14.59 on 6 and 12 degrees of freedom is 0.00007, which Table 13.11 prints as 0.000; Table 13.10 prints it as 0.01
Anova sum sq: Fixtures (F)p. 617
Book 82.80Data 82.79
The fixtures' sum of squares is 82.792 (Σy²i.../16 − y²..../48 = 32739.125 − 32656.333), as Minitab prints it in Table 14.13; 82.80 is not its rounding
Anova mean sq: Layouts (L)p. 617
Book 4.09Data 4.08
The layouts' mean square is their sum of squares on one degree of freedom, 4.083, as Table 14.13 prints it; the 4.08 beside it is that rounded, 4.09 is not
P: Operators (within layouts), O(L)p. 617
Book 0.01Data 0.00
The P-value of F = 5.137 on 6 and 24 degrees of freedom is 0.0016, as Minitab's 0.002 in Table 14.13; the table prints 0.01
P: Temperature (B)p. 623
Book 0.01Data 0.00
The P-value of F = 42.01 on 3 and 6 degrees of freedom is 0.0002; the table prints 0.01
Coefficient: Interceptp. 630
Book 49.73875Data 49.74190
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: Gap (A)p. 630
Book 10.0625Data 10.0656
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: Gas flow (B)p. 630
Book 5.6275Data 5.6244
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: Pressure (C)p. 630
Book 1.325Data 1.328
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: Time (D)p. 630
Book −2.0725Data -2.06938
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: RF power (E)p. 630
Book 5.12625Data 5.12313
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: ABp. 630
Book 7.34625Data 7.34313
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: ACp. 630
Book 1.83125Data 1.83438
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: ADp. 630
Book −3.00875Data -3.00562
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: AEp. 630
Book 6.505Data 6.502
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: BCp. 630
Book −0.60125Data -0.604375
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: BDp. 630
Book −1.35875Data -1.36188
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: BEp. 630
Book −0.2125Data -0.209375
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: CDp. 630
Book 1.86625Data 1.86938
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Coefficient: CEp. 630
Book −1.485Data -1.48813
Every coefficient of Table 14.23 differs from the fit to Table 14.22 by 0.05/16 = 0.003125, with the signs of run 12 (whole plot 6, A+ B− C+ D+ E−): they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Largest effect: subplot effects, AEp. 631
Book 13.01Data 13.00
2 × 6.50187 = 13.0037 from the fit to Table 14.22; the axis ends at twice Table 14.23's 6.505, they are the coefficients of the runs with 38.03 there, where Table 14.22 prints 38.08
Total: y3., in Txyp. 660
Book 184Data 180
Machine 3's strengths total 180, as Table 15.10 prints; the formula for Txy writes (106)(184), though its 96.00 is worked with 180
MSE: without the covariatep. 668
Book 470.82Data 470.86
The residual mean square of this model is 4708.56/10 = 470.86
Selected: different samples starredp. 676
Book 20Data 15
The starred samples hold only 15 different pairs of viscosity and molecular weight: samples 2 and 22, 4 and 24, 5 and 25, 9 and 29, and 18 and 38 are the same, and no sample with (44, 1260), (58, 1359), (33, 1275), (58.3, 1330) or (31.9, 1250) is starred; Table 15.22 holds each of the 20 different pairs once
Alias matrix: X3X4 row, 14 columnp. 677
Book −0.04Data 0.0399675
The runs of Table 15.22 give +0.040; the table prints its sign as minus
Alias matrix: X3X4 row, 24 columnp. 677
Book −0.042Data 0.0418117
The runs of Table 15.22 give +0.042; the table prints its sign as minus
Defining relation: 2^(10-6)p. 712
Book I = ABCE = BCDF = ADEF = ACDG = BDEG = ABFG = CEFG = ABDH = CDEH = ACFH = BEFH = BCGH = AEGH = DFGH = ABCDEFGH = ABCDJ = DEJ = AFJ = BCEFJ = BGJ = ACEGJ = CDFGI = ABDEFGJ = CHJ = ABEHJ = BDFHJ = ACDEFHJ = ADGHJ = BCDEGHJ = ABCFGHJ = EFGHJ = ABK = CEK = ACDFK = BDEFK = BCDGK = ADEGK = FGK = ABCEFGK = DHK = ABCDEHK = BCFHK = AEFHK = ACGHK = BEGHK = ABDFGHK = CDEFGHK = CDJK = ABDEJK = BFJK = ACEFJK = AGJK = BCEGJK = ABCDFGJK = DEFGJK = ABCHJK = EHJK = ADFHJK = BCDEFHJK = BDGHJK = ACDEGHJK = CFGHJK = ABEFGHJKData ABCDEFGH, ABCDEHK, ABCDFGJK, ABCDJ, ABCE, ABCEFGK, ABCFGHJ, ABCHJK, ABDEFGJ, ABDEJK, ABDFGHK, ABDH, ABEFGHJK, ABEHJ, ABFG, ABK, ACDEFHJ, ACDEGHJK, ACDFK, ACDG, ACEFJK, ACEGJ, ACFH, ACGHK, ADEF, ADEGK, ADFHJK, ADGHJ, AEFHK, AEGH, AFJ, AGJK, BCDEFHJK, BCDEGHJ, BCDF, BCDGK, BCEFJ, BCEGJK, BCFHK, BCGH, BDEFK, BDEG, BDFHJ, BDGHJK, BEFH, BEGHK, BFJK, BGJ, CDEFGHK, CDEH, CDFGJ, CDJK, CEFG, CEK, CFGHJK, CHJ, DEFGJK, DEJ, DFGH, DHK, EFGHJ, EHJK, FGK
The relation prints CDFGI, with I, the identity, for the factor J: the word is CDFGJ, the product of the generators' words BCDF, ACDG and ABCDJ, printed so in the relations of designs (o) and (u)
Factors: 2^(15-11)p. 717
Book 5Data 15
The heading prints 5 factors in 16 runs for 15: the label 2^(15−11) and the generators, which name the factors A to P without I, make fifteen, as Table 8.14 lists this design
Not yet
Answers the book prints that Factorial cannot compute yet, by what it lacks.
- A count from the enumeration of nonisomorphic orthogonal designs in 16 runs, which the library does not dopp. 420 and 426
- Larntz and Whitcomb's multiplier, calibrated by simulation, which the library does not computep. 264
- Yates's interblock estimate, from the block totals, which the library does not compute; the combined estimate, which is checked, uses bothp. 175
- JMP's desirability, a scaling of the prediction to its default goal, which the library does not computepp. 217 and 219
- The library's optimizer takes limits on the factors only, not on a second response, so it cannot search this problem; the response at the printed setting is checkedp. 498
Show the rest
- The library's optimizer takes limits on the factors only, not on a second response, so it cannot search for this optimum, the molecular weight held within 3200 to 3400; the response at the printed setting is checkedp. 499
- The prediction variance at a point that is not a run of the design, σ²(1 + x1² + x2² + x1²x2²)/4, which evaluate_design reports only at the design's runsp. 283
- The smallest number of samples of each formulation whose power reaches the target 0.95, a search the library does not make; it reproduces: the library's power is 0.929 at 7 and 0.9602 at 8, which is checkedp. 47
- The smallest number of samples of each formulation whose power reaches the target 0.9, a search the library does not make; it reproduces: the library's power is 0.8997 at 22 and 0.9125 at 23, which is checkedp. 47
- The library does not have (it is 0.2071 from the variances checked here)p. 85
- A step of Bartlett's test, which the library does not have: arithmetic on the group sizes (it is 1.1042)p. 85
- The library does not have (scipy.stats.bartlett gives 0.4335)p. 85
- The library does not have (scipy.stats.bartlett gives P = 0.9332, from the unrounded statistic)p. 85
- S_C1, which is checked, times √((a − 1)F0.01,3,16), from the F table, which the library does not computep. 97
- S_C2, which is checked, times √((a − 1)F0.01,3,16), from the F table, which the library does not computep. 97
- The power of the one-way analysis of variance F test at α = 0.01, σ = 25 and a largest difference of 75, which the library does not compute: evaluate_design's power is for one coefficient (scipy's noncentral F gives 0.804838)p. 108
- The same power for six replicates (scipy's noncentral F gives 0.915384); the text's choice of n = 6 followsp. 108
- The library does not draw (scipy's noncentral F gives 0.962)p. 107
- The library does not draw (scipy's noncentral F gives 0.996)p. 107
- Read from the operating characteristic curves of Appendix Chart V, which the library does not draw; Minitab's 0.915384 for six replicates is the same powerp. 108
- The Kruskal-Wallis test is not in the library; H is the treatment sum of squares of the ranks, 591.30 by the library's analysis of variance, over their variance, 34.97, which is checked: 16.907 (scipy.stats.kruskal gives 16.907)p. 129
- The Kruskal-Wallis test is not in the library (scipy.stats.kruskal gives 7.386 × 10⁻⁴)p. 129
- A step of the interval for the intraclass correlation, worked from the F table, which the library does not computep. 121
- A step of the same interval, from the F tablep. 121
- The library does not draw (scipy's noncentral F gives 0.606)p. 154
- The library does not draw (scipy's noncentral F gives 0.724)p. 154
- The library does not draw, at Φ = 1.60p. 202
- The library does not draw, at Φ = 1.96p. 202
- The library does not draw, at Φ = 2.26p. 202
- The library does not draw (scipy's noncentral F gives 0.923)p. 202
- The library does not report the correlations of its estimatesp. 268
- The inverse of B, worked from the coefficients the fit gives, is [−0.7349 −0.0918; −0.0918 −1.0102]; the library gives the stationary point it leads to, checked here, and not the inverse itselfp. 493
- 2.0 × 0.30: f_k,n = √((n − 1)/n)/d2, with d2 the mean range of k normal observations in units of σ (2.326 for k = 5), which the library does not tabulatep. 542
- 1.60 × 0.35: f_k,n = √((n − 1)/n)/d2, with d2 the mean range of k normal observations in units of σ (2.326 for k = 5), which the library does not tabulatep. 542
- F_k,n = √((n − 1)/n)/d2, with d2 the mean range of k normal observations in units of σ (for k = 5 points), which the library does not tabulatep. 544
- F_k,n = √((n − 1)/n)/d2, with d2 the mean range of k normal observations in units of σ (for k = 9 points), which the library does not tabulatep. 544
- F_k,n = √((n − 1)/n)/d2, with d2 the mean range of k normal observations in units of σ (for k = 10 points), which the library does not tabulatep. 544
- Functions of percentage points of the F distribution, from the Appendix, which the library does not computep. 601
- The library derives no expected mean squares; the coefficients are those of the balanced design's levels and replicatesp. 622
- The determinant of X'X = 4I, 4⁴; evaluate_design reports the design's D-efficiency, 100 percent, not the determinantp. 282