Search Results - Random house,

The random house guide to technical and scientific communication / by Zimmerman, Donald E.

Production and operations management : manufacturing and non-manufacturing / by Dilworth, B. James

Mastering Lean Six Sigma advanced black belt concepts / by Taghizadegan, Salman, 1957-

Table of Contents: “…Analysis of concepts and strategies: advanced statistical analysis, achieving ultimate performance scientifically -- 9.1 Descriptive statistics -- 9.1.1 Descriptive statistics techniques and graphing: stem and leaf -- 9.1.2 Histogram -- 9.1.3 Measure of center tendency -- 9.1.4 Measures of variability -- 9.2 Descriptive measures -- 9.2.1 Measurement system analysis -- 9.2.2 Accuracy/bias -- 9.2.3 Stability (consistency) -- 9.2.4 Linearity -- 9.2.5 Gage repeatability and reproducibility (or Gage R&R) -- 9.2.6 Measurement system components -- 9.3 Probability distributions and concepts -- 9.3.1 Definition, experiment, outcome, and sample space -- 9.3.2 Probability of event (EI) as relative frequency -- 9.3.3 Marginal and conditional probabilities -- 9.3.4 The rules of probability (union of events) -- 9.3.5 The rules of probability (intersection of events) -- 9.4 Discrete random variables: probability distribution -- 9.4.1 Binomial probability distribution -- 9.4.2 Poisson probability distribution -- 9.4.3 The hypergeometric probability distribution -- 9.5 Continuous random variables probability distributions -- 9.5.1 Normal probability distribution -- 9.5.2 t-distribution -- 9.5.3 Normality test -- 9.5.4 Exponential distribution -- 9.5.5 Reliability engineering -- 9.6 Inferential statistics and sampling distribution -- 9.6.1 Random sampling and the distribution of the sample mean -- 9.6.2 Central limit theorem (CLT) -- 9.6.3 Confidence interval for the mean [mu] of normal population ([theta] is known) -- 9.6.4 Confidence interval for the mean [mu] of normal -- Population (([theta] is unknown) -- 9.6.5 Selecting the necessary sample size -- 9.7 Hypothesis testing, inferences procedures, and proportions testing -- 9.7.1 Hypothesis testing for the mean [mu] and variance ([theta]2) of the population -- 9.7.2 P-value application -- 9.7.3 Hypothesis testing using p-value approach (using equal mean) -- 9.7.4 Hypothesis testing on the mean [mu] of a normal population for small sample -- 9.7.5 Inference procedures for two populations: applying the concepts -- 9.7.6 Comparing two normal population means ([mu]1 - [mu]2) using two small, independent samples: apply the mechanics -- 9.7.7 Comparing the variance of two normal populations ([theta]12-[theta]22) using independent samples-f test (small sample size): apply the mechanics -- 9.7.8 Estimation and testing for population proportions -- 9.7.9 Confidence interval for a population proportion: large sample -- 9.7.10 Hypothesis testing for a population proportion -- 9.7.11 Comparing population proportion: two large independent samples -- 9.8 Advanced analysis of variance (ANOVA) -- 9.8.1 One-way analysis of variance -- 9.8.2 Randomized block design and analysis of variance -- 9.8.3 Two-way analysis of variance -- 9.9 Linear regression analysis -- 9.9.1 Scatter plots and correlation analysis -- 9.9.2 Simple linear regression model and analysis -- 9.9.3 Linear regression model -- 9.9.4 Least square criteria -- 9.9.5 Inferences on the slope [beta]1, concept: t-test -- 9.9.6 Confidence interval for B1 slope -- 9.9.7 Prediction by regression analysis: confidence interval for an individual y, given x -- 9.10 Multiple regression analysis -- 9.10.1 Multiple linear regression model building -- 9.10.2 Hypothesis testing and confidence interval -- 9.10.3 Polynomial and nonlinear regression model building -- 9.11 Tollgate review and deliverables for analysis phase -- 9.11.1 Analysis phase deliverables and checklist --…”
An electronic book accessible through the World Wide Web; click to view

Principles of GNSS, inertial, and multisensor integrated navigation systems / by Groves, Paul D. (Paul David)

An electronic book accessible through the World Wide Web; click to view