Statistics and Probability with Applications for Engineers and Scientists Using MINITAB, R and JMP. Bhisham C. Gupta

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      1 Chapter 2Table 2.3.1 Annual revenues of 110 small to midsize companies located in mid‐wes...Table 2.3.2 Frequency distribution for the data in Table 2.3.1.Table 2.3.3 Frequency distribution table for the hospital data.Table 2.3.4 Frequency table for the data on rod lengths.Table 2.4.1 Understanding defect rates as a function of various process steps.Table 2.4.2 Frequency distribution table for the data in Example 2.4.4.Table 2.4.3 Frequency distribution table for the survival time of parts.Table 2.4.4 Lawn mowers sold by a garden shop over a period of 12 months of a gi...Table 2.4.5 Number of parts produced per week by each worker.Table 2.6.1 Age distribution of a group of 40 basketball fans watching a basketb...Table 2.9.1 Cholesterol levels and systolic BP of 10 randomly selected US males.Table 2.10.1 Turnaround time for inpatient lab testing once the swarm method was... Table 2.10.2 Physician satisfaction scores at St. Luke's Hospital before and aft...Table 2.10.3 Inpatient satisfaction scores after St. Luke's implemented the stan...

      2 Chapter 3Table 3.5.1 Classification of technicians by qualification and gender.

      3 Chapter 4Table 4.8.1 Values of

and

for

.

      4 Chapter 5Table 5.5.1 Some percentage points of the normal distribution.Table 5.10.1 Data on emissions from cars.

      5 Chapter 7Table 7.4.1 Range coefficient for various sample sizes.

      6 Chapter 9Table 9.2.1 Type I and type II errors and their probabilities of occurrence (in ...Table 9.5.1 Population variance known

      7 Chapter 10Table 10.5.1 Failure voltage (kV/mm) for two types of cable.Table 10.5.2 Failure time (in hours) in an accelerated life test of conductors.Table 10.5.3 Survival times (in weeks) of male mice.

      8 Chapter 11Table 11.4.1 Table format of the data with grid‐lines (low data‐ink ratio).Table 11.4.2 Table format of the data without grid‐lines (high data‐ink ratio).Table 11.4.3 Iris flower data (only the first few observations are shown here).Table 11.6.1 Confusion matrix for two‐class classification model.Table 11.6.2 Confusion matrix for three‐class classification model.Table 11.6.3 Confusion matrix for two‐class classification model.Table 11.6.4 Challenger O‐ring failure data.Table 11.6.5 Confusion matrix for challenger data for different cutoff values.Table 11.7.1 Sample data set with four variables.Table 11.7.2 Gini index computation for variables in Table 11.7.1.Table 11.7.3 Confusion matrix for original training data in Example 11.7.2.Table 11.7.4 Confusion matrix for randomly selected 34 Iris flowers (observation...Table 11.7.5 Stage C prostate cancer data (only the first few observations are s...

      9 Chapter 12Table 12.2.1 Reported crime data.Table 12.2.2 Euclidean distances between six US states.Table 12.2.3 A clinical trials study data.Table 12.2.4 Dichotomous attributes of the clinical trials study data.Table 12.2.5 The contingency table for patients 001 and 002 based on data from T...Table 12.2.6 The Jaccard coefficients for the pairs of patients in Table 12.2.4.Table 12.2.7 Contingency table for variables age and gender in clinical trial st...Table 12.3.1 Euclidean distances between six US states.Table 12.3.2 Updated Euclidean distances after mergingE and F. Table 12.3.3 Updated Euclidean distances after mergingEF and D. Table 12.3.4 Updated Euclidean distances after mergingDEF and C. Table 12.3.5 Euclidean distances between six US states.Table 12.3.6 Updated Euclidean distances after merging statesE and F. Table 12.3.7 Updated Euclidean distances after merging clusterEF and state D. Table 12.3.8 Updated Euclidean distances after merging clusterDEF and state C. Table 12.4.1 A two‐dimensional data set.Table 12.4.2 Summary statistics ofK‐means clusters in Example 12.4.1. Table 12.6.1 Covariance structures for model‐based clustering.Table 12.6.2 Stiffness measurements for first 13 boards.

      10 Chapter 13Table 13.2.1 Results of n observations classified into k categories. Table 13.2.2 Results and analysis of 200 throws of an icosahedral die.Table 13.2.3 Results of

      11 Chapter 14Table 14.2.1 Calculations for obtaining the value of the test statistic.Table 14.2.2

      12 Chapter 15Table 15.3.1 Fitted values and the corresponding residuals for the data in Examp...Table 15.5.1 Flow rate and percent of waste solid removed.Table 15.5.2 Certain formulas useful for computations in regression analysis.Table 15.6.1 Analysis of variance for a fitted straight line.Table 15.6.2 Analysis of variance table for the data in Table 15.5.1.Example 15.7.1 Table 15.7.1 Data on soybean crop experiment.Table 15.8.1 Data for the experiment in Example.

      13 Chapter 16Table 16.2.1 Students' placement scores and their cumulative GPAs.Table 16.3.1 ANOVA table for the fitted regression model (16.2.2).Table СКАЧАТЬ